subject:(decision tree)

Virginia Tech

1. Dalkiran, Evrim. Discrete and Continuous Nonconvex Optimization: Decision Trees, Valid Inequalities, and Reduced Basis Techniques.

Degree: PhD, Industrial and Systems Engineering, 2011, Virginia Tech

URL: http://hdl.handle.net/10919/77366

► This dissertation addresses the modeling and analysis of a strategic risk management problem via a novel decision tree optimization approach, as well as development of… (more)

▼ This dissertation addresses the modeling and analysis of a strategic risk management problem via a novel decision tree optimization approach, as well as development of enhanced Reformulation-Linearization Technique (RLT)-based linear programming (LP) relaxations for solving nonconvex polynomial programming problems, through the generation of valid inequalities and reduced representations, along with the design and implementation of efficient algorithms. We first conduct a quantitative analysis for a strategic risk management problem that involves allocating certain available failure-mitigating and consequence-alleviating resources to reduce the failure probabilities of system safety components and subsequent losses, respectively, together with selecting optimal strategic decision alternatives, in order to minimize the risk or expected loss in the event of a hazardous occurrence. Using a novel decision tree optimization approach to represent the cascading sequences of probabilistic events as controlled by key decisions and investment alternatives, the problem is modeled as a nonconvex mixed-integer 0-1 factorable program. We develop a specialized branch-and-bound algorithm in which lower bounds are computed via tight linear relaxations of the original problem that are constructed by utilizing a polyhedral outer-approximation mechanism in concert with two alternative linearization schemes having different levels of tightness and complexity. We also suggest three alternative branching schemes, each of which is proven to guarantee convergence to a global optimum for the underlying problem. Extensive computational results and sensitivity analyses are presented to provide insights and to demonstrate the efficacy of the proposed algorithm. In particular, our methodology outperformed the commercial software BARON (Version 8.1.5), yielding a more robust performance along with an 89.9% savings in effort on average. Next, we enhance RLT-based LP relaxations for polynomial programming problems by developing two classes of valid inequalities: v-semidefinite cuts and bound-grid-factor constraints. The first of these uses concepts derived from semidefinite programming. Given an RLT relaxation, we impose positive semidefiniteness on suitable dyadic variable-product matrices, and correspondingly derive implied semidefinite cuts. In the case of polynomial programs, there are several possible variants for selecting such dyadic variable-product matrices for imposing positive semidefiniteness restrictions in order to derive implied valid inequalities, which leads to a new class of cutting planes that we call v-semidefinite cuts. We explore various strategies for generating such cuts within the context of an RLT-based branch-and-cut scheme, and exhibit their relative effectiveness towards tightening the RLT relaxations and solving the underlying polynomial programming problems, using a test-bed of randomly generated instances as well as standard problems from the literature. Our results demonstrate that these cutting planes achieve a… Advisors/Committee Members: Sherali, Hanif D. (committeechair), Fraticelli, Barbara M. P. (committee member), Sarin, Subhash C. (committee member), Bish, Douglas R. (committee member).

Subjects/Keywords: Decision tree optimization; Reformulation-Lineariz

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APA (6^th Edition):

Dalkiran, E. (2011). Discrete and Continuous Nonconvex Optimization: Decision Trees, Valid Inequalities, and Reduced Basis Techniques. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/77366

Chicago Manual of Style (16^th Edition):

Dalkiran, Evrim. “Discrete and Continuous Nonconvex Optimization: Decision Trees, Valid Inequalities, and Reduced Basis Techniques.” 2011. Doctoral Dissertation, Virginia Tech. Accessed January 22, 2021. http://hdl.handle.net/10919/77366.

MLA Handbook (7^th Edition):

Dalkiran, Evrim. “Discrete and Continuous Nonconvex Optimization: Decision Trees, Valid Inequalities, and Reduced Basis Techniques.” 2011. Web. 22 Jan 2021.

Vancouver:

Dalkiran E. Discrete and Continuous Nonconvex Optimization: Decision Trees, Valid Inequalities, and Reduced Basis Techniques. [Internet] [Doctoral dissertation]. Virginia Tech; 2011. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10919/77366.

Council of Science Editors:

Dalkiran E. Discrete and Continuous Nonconvex Optimization: Decision Trees, Valid Inequalities, and Reduced Basis Techniques. [Doctoral Dissertation]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/77366

University of Alberta

2. Farhangfar, Alireza. NOVEL MACHINE LEARNING ALGORITHMS.

Degree: PhD, Department of Computing Science, 2013, University of Alberta

URL: https://era.library.ualberta.ca/files/gt54kn98f

► Many machine learning algorithms learn from the data by capturing certain interesting characteristics. Decision trees are used in many classification tasks. In some circumstances, we… (more)

▼ Many machine learning algorithms learn from the data by capturing certain interesting characteristics. Decision trees are used in many classification tasks. In some circumstances, we only want to consider fixed-depth trees. Unfortunately, finding the optimal depth-d decision tree can require time exponential in d. In the first part of this dissertation, we present OPTNBDT algorithm, which is a fast way to produce a near optimal fixed-depth decision tree under the Naıve Bayes assumption. We apply this technique to real-world datasets and find that our model improves the computational costs significantly while yielding relatively high accuracy. In the second part of this dissertation, we present two novel algorithms for active learning. There are scenarios where we have access to many unlabeled data; however, obtaining the labels for the data is difficult. An active learning process tries to address this issue by selectively requesting the label of few unlabeled instances, with the goal of using these newly labeled instances to produce an effective classifier. First, we focus on active learning for image segmentation, which requires producing a label for each pixel in an image. We provide an active learner (LMU) that first selects the image whose expected label will reduce the uncertainty of other unlabeled images the most, and then after greedily selects the most informative image. The results of our experiments, over real-world datasets show that training on very few informative images can produce a segmenter that is as good as training on the entire dataset. Finally, we present the importance sampling algorithm (ISAL) for actively learning in the standard classification framework, which we demonstrate its sample and label efficiency. In particular, on each iteration, ISAL identifies a distribution that puts large weight on instances whose labels are uncertain, then requests the label of an instance drawn from that distribution. We prove that ISAL can be more sample and label efficient than passive learning with an exponential convergence rate to the Bayes classifier on noise-free data. We also provide empirical studies that show ISAL is more effective than many other active learning algorithms.

Subjects/Keywords: Fixed-depth decision tree; Active learning

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APA (6^th Edition):

Farhangfar, A. (2013). NOVEL MACHINE LEARNING ALGORITHMS. (Doctoral Dissertation). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/gt54kn98f

Chicago Manual of Style (16^th Edition):

Farhangfar, Alireza. “NOVEL MACHINE LEARNING ALGORITHMS.” 2013. Doctoral Dissertation, University of Alberta. Accessed January 22, 2021. https://era.library.ualberta.ca/files/gt54kn98f.

MLA Handbook (7^th Edition):

Farhangfar, Alireza. “NOVEL MACHINE LEARNING ALGORITHMS.” 2013. Web. 22 Jan 2021.

Vancouver:

Farhangfar A. NOVEL MACHINE LEARNING ALGORITHMS. [Internet] [Doctoral dissertation]. University of Alberta; 2013. [cited 2021 Jan 22]. Available from: https://era.library.ualberta.ca/files/gt54kn98f.

Council of Science Editors:

Farhangfar A. NOVEL MACHINE LEARNING ALGORITHMS. [Doctoral Dissertation]. University of Alberta; 2013. Available from: https://era.library.ualberta.ca/files/gt54kn98f

Vanderbilt University

3. Hei, Songtao. A Decision Tree Based Approach to Filter Candidates for Software Engineering Jobs Using GitHub Data.

Degree: MS, Computer Science, 2015, Vanderbilt University

URL: http://hdl.handle.net/1803/11151

► A challenge for companies hiring software engineers is the large number of candidate profiles on LinkedIn, Monster.com, and other job websites and the inability to… (more)

▼ A challenge for companies hiring software engineers is the large number of candidate profiles on LinkedIn, Monster.com, and other job websites and the inability to easily filter top candidates from these lists. In this paper, we propose a novel approach for utilizing the social network structure in GitHub and a decision tree algorithm to solve this problem efficiently and filter candidate software engineers. The approach is based off the idea that the centrality value of a node (i.e., candidate engineer) in the graph of GitHub users is an approximate indicator of the value of the programmer. To reduce the number of candidates that are considered in a job selection process, a threshold centrality value can be used to filter job candidates based on their importance in the GitHub user graph. A challenge with this approach is that, since GitHub has millions of users, calculating the centrality for every node in the GitHub user graph is an expensive operation. To overcome this challenge, we train a decision tree to predict a user’s centrality based on a limited subset of their attributes. To generate training data for the decision tree from the unlabeled GitHub user graph, a threshold centrality value is chosen and a part of the user graph is labeled with Accepted or Rejected based on whether or not the corresponding user meets the threshold centrality. We also collect the total number of the each kind of public GitHub event each user has generated and we use the number of these GitHub events as training attributes for each user in the training dataset. Once decision trees are built with this training dataset, recruiters can use these decision trees to process large quantities of software engineering job candidates and to improve the judgment of HR departments. Based on empirical results from experiments that we conducted with GitHub user data, our approach can reach a precision of 96%. Moreover, this method saves future expensive network centrality computation as the GitHub social graph changes over time. Advisors/Committee Members: Christopher Jules White (committee member), Douglas C. Schmidt (committee member).

Subjects/Keywords: GitHub; Algorithmic recruiting; machine learning; decision tree

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APA (6^th Edition):

Hei, S. (2015). A Decision Tree Based Approach to Filter Candidates for Software Engineering Jobs Using GitHub Data. (Thesis). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/11151

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Hei, Songtao. “A Decision Tree Based Approach to Filter Candidates for Software Engineering Jobs Using GitHub Data.” 2015. Thesis, Vanderbilt University. Accessed January 22, 2021. http://hdl.handle.net/1803/11151.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Hei, Songtao. “A Decision Tree Based Approach to Filter Candidates for Software Engineering Jobs Using GitHub Data.” 2015. Web. 22 Jan 2021.

Vancouver:

Hei S. A Decision Tree Based Approach to Filter Candidates for Software Engineering Jobs Using GitHub Data. [Internet] [Thesis]. Vanderbilt University; 2015. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/1803/11151.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Hei S. A Decision Tree Based Approach to Filter Candidates for Software Engineering Jobs Using GitHub Data. [Thesis]. Vanderbilt University; 2015. Available from: http://hdl.handle.net/1803/11151

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Iowa State University

4. Bennette, Walter Dean. Instance selection for simplified decision trees through the generation and selection of instance candidate subsets.

Degree: 2011, Iowa State University

URL: https://lib.dr.iastate.edu/etd/12084

► Decision trees are a useful tool to help in the extraction of information from databases, but all too often this ability is clouded by the… (more)

Subjects/Keywords: decision tree; instance selection; simplified; Industrial Engineering

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APA (6^th Edition):

Bennette, W. D. (2011). Instance selection for simplified decision trees through the generation and selection of instance candidate subsets. (Thesis). Iowa State University. Retrieved from https://lib.dr.iastate.edu/etd/12084

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Bennette, Walter Dean. “Instance selection for simplified decision trees through the generation and selection of instance candidate subsets.” 2011. Thesis, Iowa State University. Accessed January 22, 2021. https://lib.dr.iastate.edu/etd/12084.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Bennette, Walter Dean. “Instance selection for simplified decision trees through the generation and selection of instance candidate subsets.” 2011. Web. 22 Jan 2021.

Vancouver:

Bennette WD. Instance selection for simplified decision trees through the generation and selection of instance candidate subsets. [Internet] [Thesis]. Iowa State University; 2011. [cited 2021 Jan 22]. Available from: https://lib.dr.iastate.edu/etd/12084.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Bennette WD. Instance selection for simplified decision trees through the generation and selection of instance candidate subsets. [Thesis]. Iowa State University; 2011. Available from: https://lib.dr.iastate.edu/etd/12084

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Kansas State University

5. Whitley, Michael Aaron. Using statistical learning to predict survival of passengers on the RMS Titanic.

Degree: MS, Statistics, 2015, Kansas State University

URL: http://hdl.handle.net/2097/20541

► When exploring data, predictive analytics techniques have proven to be effective. In this report, the efficiency of several predictive analytics methods are explored. During the… (more)

Subjects/Keywords: Decision tree; Ensemble; Kaggle; Titanic; Statistics (0463)

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APA (6^th Edition):

Whitley, M. A. (2015). Using statistical learning to predict survival of passengers on the RMS Titanic. (Masters Thesis). Kansas State University. Retrieved from http://hdl.handle.net/2097/20541

Chicago Manual of Style (16^th Edition):

Whitley, Michael Aaron. “Using statistical learning to predict survival of passengers on the RMS Titanic.” 2015. Masters Thesis, Kansas State University. Accessed January 22, 2021. http://hdl.handle.net/2097/20541.

MLA Handbook (7^th Edition):

Whitley, Michael Aaron. “Using statistical learning to predict survival of passengers on the RMS Titanic.” 2015. Web. 22 Jan 2021.

Vancouver:

Whitley MA. Using statistical learning to predict survival of passengers on the RMS Titanic. [Internet] [Masters thesis]. Kansas State University; 2015. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/2097/20541.

Council of Science Editors:

Whitley MA. Using statistical learning to predict survival of passengers on the RMS Titanic. [Masters Thesis]. Kansas State University; 2015. Available from: http://hdl.handle.net/2097/20541

University of Maryland

6. Filimonov, Denis. Decision Tree-based Syntactic Language Modeling.

Degree: Computer Science, 2011, University of Maryland

URL: http://hdl.handle.net/1903/12215

► Statistical Language Modeling is an integral part of many natural language processing applications, such as Automatic Speech Recognition (ASR) and Machine Translation. N-gram language models… (more)

▼ Statistical Language Modeling is an integral part of many natural language processing applications, such as Automatic Speech Recognition (ASR) and Machine Translation. N-gram language models dominate the field, despite having an extremely shallow view of language – a Markov chain of words. In this thesis, we develop and evaluate a joint language model that incorporates syntactic and lexical information in a effort to ``put language back into language modeling.'' Our main goal is to demonstrate that such a model is not only effective but can be made scalable and tractable. We utilize decision trees to tackle the problem of sparse parameter estimation which is exacerbated by the use of syntactic information jointly with word context. While decision trees have been previously applied to language modeling, there has been little analysis of factors affecting decision tree induction and probability estimation for language modeling. In this thesis, we analyze several aspects that affect decision tree-based language modeling, with an emphasis on syntactic language modeling. We then propose improvements to the decision tree induction algorithm based on our analysis, as well as the methods for constructing forest models – models consisting of multiple decision trees. Finally, we evaluate the impact of our syntactic language model on large scale Speech Recognition and Machine Translation tasks. In this thesis, we also address a number of engineering problems associated with the joint syntactic language model in order to make it tractable. Particularly, we propose a novel decoding algorithm that exploits the decision tree structure to eliminate unnecessary computation. We also propose and evaluate an approximation of our syntactic model by word n-grams – the approximation that makes it possible to incorporate our model directly into the CDEC Machine Translation decoder rather than using the model for rescoring hypotheses produced using an n-gram model. Advisors/Committee Members: Harper, Mary P (advisor), Resnik, Philip (advisor).

Subjects/Keywords: Computer science; decision tree; syntactic language model

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Filimonov, D. (2011). Decision Tree-based Syntactic Language Modeling. (Thesis). University of Maryland. Retrieved from http://hdl.handle.net/1903/12215

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Filimonov, Denis. “Decision Tree-based Syntactic Language Modeling.” 2011. Thesis, University of Maryland. Accessed January 22, 2021. http://hdl.handle.net/1903/12215.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Filimonov, Denis. “Decision Tree-based Syntactic Language Modeling.” 2011. Web. 22 Jan 2021.

Vancouver:

Filimonov D. Decision Tree-based Syntactic Language Modeling. [Internet] [Thesis]. University of Maryland; 2011. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/1903/12215.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Filimonov D. Decision Tree-based Syntactic Language Modeling. [Thesis]. University of Maryland; 2011. Available from: http://hdl.handle.net/1903/12215

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

New Jersey Institute of Technology

7. Liu, Haoyue. Decision tree rule-based feature selection for imbalanced data.

Degree: MSin Computer Engineering - (M.S.), Electrical and Computer Engineering, 2017, New Jersey Institute of Technology

URL: https://digitalcommons.njit.edu/theses/25

► A class imbalance problem appears in many real world applications, e.g., fault diagnosis, text categorization and fraud detection. When dealing with an imbalanced dataset,… (more)

Subjects/Keywords: Imbalanced data; Decision tree; Computer Engineering

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APA (6^th Edition):

Liu, H. (2017). Decision tree rule-based feature selection for imbalanced data. (Thesis). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/theses/25

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Liu, Haoyue. “Decision tree rule-based feature selection for imbalanced data.” 2017. Thesis, New Jersey Institute of Technology. Accessed January 22, 2021. https://digitalcommons.njit.edu/theses/25.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Liu, Haoyue. “Decision tree rule-based feature selection for imbalanced data.” 2017. Web. 22 Jan 2021.

Vancouver:

Liu H. Decision tree rule-based feature selection for imbalanced data. [Internet] [Thesis]. New Jersey Institute of Technology; 2017. [cited 2021 Jan 22]. Available from: https://digitalcommons.njit.edu/theses/25.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Liu H. Decision tree rule-based feature selection for imbalanced data. [Thesis]. New Jersey Institute of Technology; 2017. Available from: https://digitalcommons.njit.edu/theses/25

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

NSYSU

8. Lin, Yi-chun. Applying Decision Tree to Optimize Online Trading Audit Strategy.

Degree: Master, Finance, 2018, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0610118-235652

► Development of the internet technology is advancing, and the proportion of online shopping greatly increased. According to the declaration of business tax data by online… (more)

Subjects/Keywords: Online Trading Audit Strategy; Classification and Regression Tree (CART); Decision Tree

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APA (6^th Edition):

Lin, Y. (2018). Applying Decision Tree to Optimize Online Trading Audit Strategy. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0610118-235652

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Lin, Yi-chun. “Applying Decision Tree to Optimize Online Trading Audit Strategy.” 2018. Thesis, NSYSU. Accessed January 22, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0610118-235652.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Lin, Yi-chun. “Applying Decision Tree to Optimize Online Trading Audit Strategy.” 2018. Web. 22 Jan 2021.

Vancouver:

Lin Y. Applying Decision Tree to Optimize Online Trading Audit Strategy. [Internet] [Thesis]. NSYSU; 2018. [cited 2021 Jan 22]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0610118-235652.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lin Y. Applying Decision Tree to Optimize Online Trading Audit Strategy. [Thesis]. NSYSU; 2018. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0610118-235652

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Houston

9. Amalaman, Paul K. 1966-. New Approaches to Hierarchical Modeling — Frameworks, Algorithms, and Applications.

Degree: PhD, Computer Science, 2015, University of Houston

URL: http://hdl.handle.net/10657/4888

► Obtaining hierarchical organizations of knowledge is important in many domains. To create such hierarchies, improved techniques for subdividing entities hierarchically ac-cording to similarities and differences… (more)

▼ Obtaining hierarchical organizations of knowledge is important in many domains. To create such hierarchies, improved techniques for subdividing entities hierarchically ac-cording to similarities and differences are needed. New techniques for organizing docu-ments in hierarchies, for automatic document retrieval and for hierarchical query cluster-ing are being made available at a fast pace. In this work, we investigate new methods to induce hierarchical models with the goal of obtaining better predictive models, to facili-tate the creation of background knowledge with respect to an underlining class distribu-tion, to obtain hierarchical groupings of a set of objects based on background knowledge they share, to detect sub-classes within existing class distribution, and to provide methods to evaluate hierarchical groupings. The results of this effort has led to the development of (1) TPRTI, a new regression tree induction approach which uses turning points, candi-dates split points computed before the recursive process takes place, to recursively split the node datasets; (2) PATHFINDER, a new classification tree induction capable of in-ducing very short trees with high accuracies for the price of not classifying examples deemed difficult to classify; (3) AVALANCHE, a new hierarchical divisive clustering approach which takes as input a distance matrix and forms clusters maximizing inter-cluster distances; (4) STAXAC, a new agglomerative clustering approach which creates supervised taxonomies that unlike traditional agglomerative clustering, which only uses proximity as the single criterion for merging, uses both proximity and class labels infor-mation to obtain hierarchical groupings of a set of objects. We applied the techniques we developed, (1) to molecular phylogenetic-based taxonomy generation and found that this new approach and the obtained supervised taxonomies can help biologists better charac-terize organisms according to some characteristics of interest such as diseases, growth rate, etc.; (2) to data editing; we were able to enhance the accuracy of the k-nearest neighbor classifier by removing minority class examples from clusters that were extracted from a supervised taxonomy; (3) to meta learning; we developed new algorithms that operate on supervised taxonomies and compute both the distribution of the classes within a dataset, and the difficulty of classifying examples belonging to a particular dataset. Advisors/Committee Members: Eick, Christoph F. (advisor), Vilalta, Ricardo (committee member), Shi, Weidong (committee member), Shah, Shishir Kirit (committee member), Cooper, Timothy F. (committee member).

Subjects/Keywords: Decision trees; Regression tree; Classification tree; Supervised taxonomy; Hierarchical clustering

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APA (6^th Edition):

Amalaman, P. K. 1. (2015). New Approaches to Hierarchical Modeling — Frameworks, Algorithms, and Applications. (Doctoral Dissertation). University of Houston. Retrieved from http://hdl.handle.net/10657/4888

Chicago Manual of Style (16^th Edition):

Amalaman, Paul K 1966-. “New Approaches to Hierarchical Modeling — Frameworks, Algorithms, and Applications.” 2015. Doctoral Dissertation, University of Houston. Accessed January 22, 2021. http://hdl.handle.net/10657/4888.

MLA Handbook (7^th Edition):

Amalaman, Paul K 1966-. “New Approaches to Hierarchical Modeling — Frameworks, Algorithms, and Applications.” 2015. Web. 22 Jan 2021.

Vancouver:

Amalaman PK1. New Approaches to Hierarchical Modeling — Frameworks, Algorithms, and Applications. [Internet] [Doctoral dissertation]. University of Houston; 2015. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10657/4888.

Council of Science Editors:

Amalaman PK1. New Approaches to Hierarchical Modeling — Frameworks, Algorithms, and Applications. [Doctoral Dissertation]. University of Houston; 2015. Available from: http://hdl.handle.net/10657/4888

University of Texas – Austin

10. Wang, Tianyang. Multivariate real options valuation.

Degree: PhD, Information, Risk and Operations Management, 2011, University of Texas – Austin

URL: http://hdl.handle.net/2152/ETD-UT-2011-05-2797

► This dissertation research focuses on modeling and evaluating multivariate uncertainties and the dependency between the uncertainties. Managing risk and making strategic decisions under uncertainty is… (more)

▼ This dissertation research focuses on modeling and evaluating multivariate uncertainties and the dependency between the uncertainties. Managing risk and making strategic decisions under uncertainty is critically important for both individual and corporate success. In this dissertation research, we present two new methodologies, the implied binomial tree approach and the dependent decision tree approach, to modeling multivariate decision making problems with practical applications in real options valuation. First, we present the implied binomial tree approach to consolidate the representation of multiple sources of uncertainty into univariate uncertainty, while capturing the impact of these uncertainties on the project’s cash flows. This approach provides a nonparametric extension of the approaches in the literature by allowing the project value to follow a generalized diffusion process in which the volatility may vary with time and with the asset prices, therefore offering more modeling flexibility. This approach was motivated by the Implied Binomial Tree (IBT) approach that is widely used to value complex financial options. By constructing the implied recombining binomial tree in a way so as to be consistent with the simulated market information, we extended the finance-based IBT method for real options valuation — when the options are contingent on the value of one or more market related uncertainties that are not traded assets. Further, we present a general framework based on copulas for modeling dependent multivariate uncertainties through the use of a decision tree. The proposed dependent decision tree model allows multiple dependent uncertainties with arbitrary marginal distributions to be represented in a decision tree with a sequence of conditional probability distributions. This general framework could be naturally applied in decision analysis and real options valuations, as well as in more general applications of dependent probability trees. While this approach to modeling dependencies can be based on several popular copula families as we illustrate, we focus on the use of the normal copula and present an efficient computational method for multivariate decision and risk analysis that can be standardized for convenient application. Advisors/Committee Members: Dyer, James S. (advisor), Tompaidis, Efstathios (committee member), Muthuraman, Kumar (committee member), Bickel, J. E. (committee member), Butler, John C. (committee member), Garlappi, Lorenzo (committee member).

Subjects/Keywords: Real options; Decision tree; Copulas; Dependence; Evaluating uncertainties; Implied binomial tree

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APA (6^th Edition):

Wang, T. (2011). Multivariate real options valuation. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2011-05-2797

Chicago Manual of Style (16^th Edition):

Wang, Tianyang. “Multivariate real options valuation.” 2011. Doctoral Dissertation, University of Texas – Austin. Accessed January 22, 2021. http://hdl.handle.net/2152/ETD-UT-2011-05-2797.

MLA Handbook (7^th Edition):

Wang, Tianyang. “Multivariate real options valuation.” 2011. Web. 22 Jan 2021.

Vancouver:

Wang T. Multivariate real options valuation. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2011. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/2152/ETD-UT-2011-05-2797.

Council of Science Editors:

Wang T. Multivariate real options valuation. [Doctoral Dissertation]. University of Texas – Austin; 2011. Available from: http://hdl.handle.net/2152/ETD-UT-2011-05-2797

Brno University of Technology

11. Krejčířová, Magda. Návrh na implementaci metodiky rozhodovacího stromu při investičním rozhodování ve firmě: Proposal for Implementation of the Decision Tree’s Method in Context with Investment Decisions.

Degree: 2019, Brno University of Technology

URL: http://hdl.handle.net/11012/25183

► This master's thesis concerns the use of the methodology of the decision tree in the investment decision making. The proposed decision model provides the best… (more)

Subjects/Keywords: Rozhodování; rozhodovací strom; pravděpodobnost; investice; riziko; Decision; decision tree; probability; investment; risk

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Krejčířová, M. (2019). Návrh na implementaci metodiky rozhodovacího stromu při investičním rozhodování ve firmě: Proposal for Implementation of the Decision Tree’s Method in Context with Investment Decisions. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/25183

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Krejčířová, Magda. “Návrh na implementaci metodiky rozhodovacího stromu při investičním rozhodování ve firmě: Proposal for Implementation of the Decision Tree’s Method in Context with Investment Decisions.” 2019. Thesis, Brno University of Technology. Accessed January 22, 2021. http://hdl.handle.net/11012/25183.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Krejčířová, Magda. “Návrh na implementaci metodiky rozhodovacího stromu při investičním rozhodování ve firmě: Proposal for Implementation of the Decision Tree’s Method in Context with Investment Decisions.” 2019. Web. 22 Jan 2021.

Vancouver:

Krejčířová M. Návrh na implementaci metodiky rozhodovacího stromu při investičním rozhodování ve firmě: Proposal for Implementation of the Decision Tree’s Method in Context with Investment Decisions. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/11012/25183.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Krejčířová M. Návrh na implementaci metodiky rozhodovacího stromu při investičním rozhodování ve firmě: Proposal for Implementation of the Decision Tree’s Method in Context with Investment Decisions. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/25183

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Texas State University – San Marcos

12. Phillips, Clark Raymond. Employing an Efficient and Scalable Implementation of the Cost Sensitive Alternating Decision Tree algorithm to Efficiently Link Person Records.

Degree: MS, Computer Science, 2015, Texas State University – San Marcos

URL: https://digital.library.txstate.edu/handle/10877/5576

► When collecting person records for census, identifying individuals accurately is paramount. Over time, people change their phone numbers, their addresses, even their names. Without a… (more)

Subjects/Keywords: Decision trees; Machine learning; Alternating decision tree; Computer science – Mathematics; Combinatorial analysis

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Phillips, C. R. (2015). Employing an Efficient and Scalable Implementation of the Cost Sensitive Alternating Decision Tree algorithm to Efficiently Link Person Records. (Masters Thesis). Texas State University – San Marcos. Retrieved from https://digital.library.txstate.edu/handle/10877/5576

Chicago Manual of Style (16^th Edition):

Phillips, Clark Raymond. “Employing an Efficient and Scalable Implementation of the Cost Sensitive Alternating Decision Tree algorithm to Efficiently Link Person Records.” 2015. Masters Thesis, Texas State University – San Marcos. Accessed January 22, 2021. https://digital.library.txstate.edu/handle/10877/5576.

MLA Handbook (7^th Edition):

Phillips, Clark Raymond. “Employing an Efficient and Scalable Implementation of the Cost Sensitive Alternating Decision Tree algorithm to Efficiently Link Person Records.” 2015. Web. 22 Jan 2021.

Vancouver:

Phillips CR. Employing an Efficient and Scalable Implementation of the Cost Sensitive Alternating Decision Tree algorithm to Efficiently Link Person Records. [Internet] [Masters thesis]. Texas State University – San Marcos; 2015. [cited 2021 Jan 22]. Available from: https://digital.library.txstate.edu/handle/10877/5576.

Council of Science Editors:

Phillips CR. Employing an Efficient and Scalable Implementation of the Cost Sensitive Alternating Decision Tree algorithm to Efficiently Link Person Records. [Masters Thesis]. Texas State University – San Marcos; 2015. Available from: https://digital.library.txstate.edu/handle/10877/5576

NSYSU

13. Lin, Ming-Shiun. The Research of Quality Prediction Model for Touch Panel Manufacturing.

Degree: Master, Information Management, 2013, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0612113-162515

► Improving manufacturing yield is the major concern of IT manufacturing industry IIn panel manufacturing industry, large-size panels are no longer a priority due to the… (more)

Subjects/Keywords: Processes; C4.5; Decision tree; J48; Touch Panel; Data mining

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APA (6^th Edition):

Lin, M. (2013). The Research of Quality Prediction Model for Touch Panel Manufacturing. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0612113-162515

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Lin, Ming-Shiun. “The Research of Quality Prediction Model for Touch Panel Manufacturing.” 2013. Thesis, NSYSU. Accessed January 22, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0612113-162515.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Lin, Ming-Shiun. “The Research of Quality Prediction Model for Touch Panel Manufacturing.” 2013. Web. 22 Jan 2021.

Vancouver:

Lin M. The Research of Quality Prediction Model for Touch Panel Manufacturing. [Internet] [Thesis]. NSYSU; 2013. [cited 2021 Jan 22]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0612113-162515.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lin M. The Research of Quality Prediction Model for Touch Panel Manufacturing. [Thesis]. NSYSU; 2013. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0612113-162515

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

NSYSU

14. Cheng, Yuan-Chung. The Application of Fuzzy Decision Trees in Data Mining - Using Taiwan Stock Market as An Example.

Degree: Master, Information Management, 2002, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0618102-163954

► Taiwan stock market exists a special feature that over 80% of participants are natural persons while only 20% are legal persons. Compared to the latter,… (more)

Subjects/Keywords: Fuzzy decision tree; Data mining

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APA (6^th Edition):

Cheng, Y. (2002). The Application of Fuzzy Decision Trees in Data Mining - Using Taiwan Stock Market as An Example. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0618102-163954

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Cheng, Yuan-Chung. “The Application of Fuzzy Decision Trees in Data Mining - Using Taiwan Stock Market as An Example.” 2002. Thesis, NSYSU. Accessed January 22, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0618102-163954.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Cheng, Yuan-Chung. “The Application of Fuzzy Decision Trees in Data Mining - Using Taiwan Stock Market as An Example.” 2002. Web. 22 Jan 2021.

Vancouver:

Cheng Y. The Application of Fuzzy Decision Trees in Data Mining - Using Taiwan Stock Market as An Example. [Internet] [Thesis]. NSYSU; 2002. [cited 2021 Jan 22]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0618102-163954.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Cheng Y. The Application of Fuzzy Decision Trees in Data Mining - Using Taiwan Stock Market as An Example. [Thesis]. NSYSU; 2002. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0618102-163954

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

NSYSU

15. Chao, Ying. Evaluation of Sustainable Ecotourism in Chiku using System Dynamics.

Degree: Master, Marine Environment and Engineering, 2016, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0516116-154324

► Ecotourism is a concept that is getting more and more attention worldwide. Chiku wetland has many functions and values, and its cultivation, salt industries, special… (more)

Subjects/Keywords: Decision Tree; DSR Framework; Monte Carlo; System Dynamics; Wetland Ecotourism

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APA (6^th Edition):

Chao, Y. (2016). Evaluation of Sustainable Ecotourism in Chiku using System Dynamics. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0516116-154324

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Chao, Ying. “Evaluation of Sustainable Ecotourism in Chiku using System Dynamics.” 2016. Thesis, NSYSU. Accessed January 22, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0516116-154324.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Chao, Ying. “Evaluation of Sustainable Ecotourism in Chiku using System Dynamics.” 2016. Web. 22 Jan 2021.

Vancouver:

Chao Y. Evaluation of Sustainable Ecotourism in Chiku using System Dynamics. [Internet] [Thesis]. NSYSU; 2016. [cited 2021 Jan 22]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0516116-154324.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chao Y. Evaluation of Sustainable Ecotourism in Chiku using System Dynamics. [Thesis]. NSYSU; 2016. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0516116-154324

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

NSYSU

16. Chueh, Sheng-chieh. Enhanced Index Fund Performance Analysis using the Classification and Regression Tree Factor Timing Model.

Degree: Master, Finance, 2018, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0029118-164615

► There is much literature in the field of investment using the Classification and Regression Trees (CART) model to select stocks and construct a portfolio built… (more)

Subjects/Keywords: CART; Decision Tree; Enhanced Index Fund; Factor Timing

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APA (6^th Edition):

Chueh, S. (2018). Enhanced Index Fund Performance Analysis using the Classification and Regression Tree Factor Timing Model. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0029118-164615

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Chueh, Sheng-chieh. “Enhanced Index Fund Performance Analysis using the Classification and Regression Tree Factor Timing Model.” 2018. Thesis, NSYSU. Accessed January 22, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0029118-164615.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Chueh, Sheng-chieh. “Enhanced Index Fund Performance Analysis using the Classification and Regression Tree Factor Timing Model.” 2018. Web. 22 Jan 2021.

Vancouver:

Chueh S. Enhanced Index Fund Performance Analysis using the Classification and Regression Tree Factor Timing Model. [Internet] [Thesis]. NSYSU; 2018. [cited 2021 Jan 22]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0029118-164615.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chueh S. Enhanced Index Fund Performance Analysis using the Classification and Regression Tree Factor Timing Model. [Thesis]. NSYSU; 2018. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0029118-164615

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Alberta

17. Heydari, Maysam. Prognosis of Glioblastoma Multiforme Using Textural Properties on MRI.

Degree: MS, Department of Computing Science, 2009, University of Alberta

URL: https://era.library.ualberta.ca/files/bv73c2154

► This thesis addresses the challenge of prognosis, in terms of survival prediction, for patients with Glioblastoma Multiforme brain tumors. Glioblastoma is the most malignant brain… (more)

Subjects/Keywords: prognosis; machine learning; MRI; GBM; texture; survival; glioblastoma; decision tree

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Heydari, M. (2009). Prognosis of Glioblastoma Multiforme Using Textural Properties on MRI. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/bv73c2154

Chicago Manual of Style (16^th Edition):

Heydari, Maysam. “Prognosis of Glioblastoma Multiforme Using Textural Properties on MRI.” 2009. Masters Thesis, University of Alberta. Accessed January 22, 2021. https://era.library.ualberta.ca/files/bv73c2154.

MLA Handbook (7^th Edition):

Heydari, Maysam. “Prognosis of Glioblastoma Multiforme Using Textural Properties on MRI.” 2009. Web. 22 Jan 2021.

Vancouver:

Heydari M. Prognosis of Glioblastoma Multiforme Using Textural Properties on MRI. [Internet] [Masters thesis]. University of Alberta; 2009. [cited 2021 Jan 22]. Available from: https://era.library.ualberta.ca/files/bv73c2154.

Council of Science Editors:

Heydari M. Prognosis of Glioblastoma Multiforme Using Textural Properties on MRI. [Masters Thesis]. University of Alberta; 2009. Available from: https://era.library.ualberta.ca/files/bv73c2154

Universidade do Rio Grande do Sul

18. Riffel, Eduardo Samuel. Metodologias para mapeamento de suscetibilidade a movimentos de massa.

Degree: 2017, Universidade do Rio Grande do Sul

URL: http://hdl.handle.net/10183/171427

►

O mapeamento de áreas com predisposição à ocorrência de eventos adversos, que resultam em ameaça e danos a sociedade, é uma demanda de elevada importância,… (more)

▼

O mapeamento de áreas com predisposição à ocorrência de eventos adversos, que resultam em ameaça e danos a sociedade, é uma demanda de elevada importância, principalmente pelo papel que exerce em ações de planejamento, gestão ambiental, territorial e de riscos. Diante disso, este trabalho busca contribuir na qualificação de metodologias e parâmetros morfométricos para mapeamento de suscetibilidade a movimentos de massa através de SIG e Sensoriamento Remoto, um dos objetivos é aplicar e comparar metodologias de suscetibilidade a movimentos de massa, entre elas o Shalstab, e a Árvore de Decisão que ainda é pouco utilizada nessa área. Buscando um consenso acerca da literatura, fez-se necessário organizar as informações referentes aos eventos adversos através de classificação, para isso foram revisados os conceitos relacionados com desastres, tais como suscetibilidade, vulnerabilidade, perigo e risco. Também foi realizado um estudo no município de Três Coroas – RS, onde foram relacionadas as ocorrências de movimentos de massa e as zonas de risco da CPRM. A partir de parâmetros morfométricos, foram identificados padrões de ocorrência de deslizamentos, e a contribuição de fatores como uso, ocupação e declividade. Por fim, foram comparados dois métodos de mapeamento de suscetibilidade, o modelo Shalstab e a Árvore de Decisão. Como dado de entrada dos modelos foram utilizados parâmetros morfométricos, extraídos de imagens SRTM, e amostras de deslizamentos, identificadas por meio de imagens de satélite de alta resolução espacial. A comparação das metodologias e a análise da acurácia obteve uma resposta melhor para a Árvore de Decisão. A diferença, entretanto, foi pouco significativa e ambos podem representar de forma satisfatória o mapa de suscetibilidade. No entanto, o Shalstab apresentou mais limitações, devido à necessidade de dados de maior resolução espacial. A aplicação de metodologias utilizando SIG e Sensoriamento Remoto contribuíram com uma maior qualificação em relação à prevenção de danos ocasionados por movimentos de massa. Ressalta-se, entretanto, a necessidade de inventários consistentes, para obter uma maior confiabilidade na aplicação dos modelos.

The mapping of areas with predisposition to adverse events, which result in threat and damage to society, is a demand of great importance, mainly for the role it plays in planning, environmental, territorial and risk management actions. Therefore, this work seeks to contribute to the qualification of methodologies and morphometric parameters for mapping susceptibility to mass movements through GIS and Remote Sensing, one of the objectives is to apply and compare methodologies of susceptibility to mass movements, among them Shalstab, and the Decision Tree that is still little used in this area. Seeking a consensus about the literature, it was necessary to organize the information regarding the adverse events through classification, for this the concepts related to disasters such as susceptibility, vulnerability, danger and risk were reviewed. A study was also…

Advisors/Committee Members: Guasselli, Laurindo Antônio.

Subjects/Keywords: Landslides; Deslizamento; Desastres; Decision Tree; Shalstab; Geoprocessamento; Geoprocessing; Disasters

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APA (6^th Edition):

Riffel, E. S. (2017). Metodologias para mapeamento de suscetibilidade a movimentos de massa. (Thesis). Universidade do Rio Grande do Sul. Retrieved from http://hdl.handle.net/10183/171427

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Riffel, Eduardo Samuel. “Metodologias para mapeamento de suscetibilidade a movimentos de massa.” 2017. Thesis, Universidade do Rio Grande do Sul. Accessed January 22, 2021. http://hdl.handle.net/10183/171427.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Riffel, Eduardo Samuel. “Metodologias para mapeamento de suscetibilidade a movimentos de massa.” 2017. Web. 22 Jan 2021.

Vancouver:

Riffel ES. Metodologias para mapeamento de suscetibilidade a movimentos de massa. [Internet] [Thesis]. Universidade do Rio Grande do Sul; 2017. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10183/171427.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Riffel ES. Metodologias para mapeamento de suscetibilidade a movimentos de massa. [Thesis]. Universidade do Rio Grande do Sul; 2017. Available from: http://hdl.handle.net/10183/171427

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

NSYSU

19. Hsu, Yung-Cheng. Using Decision Tree Algorithm for the Detection and Decision Rule Construction of Defect on Dispensing Process.

Degree: Master, Information Management, 2018, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0419118-080930

► In recent years, due to the advancement of information technology, the analysis and research of big data has been widely applied in various industrial fields.… (more)

Subjects/Keywords: C5.0; Decision tree; Random forest; Data mining; Logistic regression

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Hsu, Y. (2018). Using Decision Tree Algorithm for the Detection and Decision Rule Construction of Defect on Dispensing Process. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0419118-080930

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Hsu, Yung-Cheng. “Using Decision Tree Algorithm for the Detection and Decision Rule Construction of Defect on Dispensing Process.” 2018. Thesis, NSYSU. Accessed January 22, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0419118-080930.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Hsu, Yung-Cheng. “Using Decision Tree Algorithm for the Detection and Decision Rule Construction of Defect on Dispensing Process.” 2018. Web. 22 Jan 2021.

Vancouver:

Hsu Y. Using Decision Tree Algorithm for the Detection and Decision Rule Construction of Defect on Dispensing Process. [Internet] [Thesis]. NSYSU; 2018. [cited 2021 Jan 22]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0419118-080930.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Hsu Y. Using Decision Tree Algorithm for the Detection and Decision Rule Construction of Defect on Dispensing Process. [Thesis]. NSYSU; 2018. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0419118-080930

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Georgia

20. Xu, Kemin. Prediction of crime categories in San Francisco area.

Degree: 2017, University of Georgia

URL: http://hdl.handle.net/10724/36563

► Numerous information and data now are available to us with an increasing development of the Internet. Even though with so much useful and valuable information… (more)

Subjects/Keywords: Statistics; Crime; San Francisco; Decision Tree; Random Forest; Logistic Regression

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Xu, K. (2017). Prediction of crime categories in San Francisco area. (Thesis). University of Georgia. Retrieved from http://hdl.handle.net/10724/36563

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Xu, Kemin. “Prediction of crime categories in San Francisco area.” 2017. Thesis, University of Georgia. Accessed January 22, 2021. http://hdl.handle.net/10724/36563.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Xu, Kemin. “Prediction of crime categories in San Francisco area.” 2017. Web. 22 Jan 2021.

Vancouver:

Xu K. Prediction of crime categories in San Francisco area. [Internet] [Thesis]. University of Georgia; 2017. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10724/36563.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Xu K. Prediction of crime categories in San Francisco area. [Thesis]. University of Georgia; 2017. Available from: http://hdl.handle.net/10724/36563

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Anna University

21. Yamini C. Effective multiple criterion approach for building a rule based decision tree classifier;.

Degree: Effective multiple criterion approach for building a rule based decision tree classifier, 2015, Anna University

URL: http://shodhganga.inflibnet.ac.in/handle/10603/49373

►

The reliability of disease classification for medical dataset has newlinebecome challenging task due to the measurement of noise and biological newlineheterogeneity among patients Most of… (more)

Subjects/Keywords: decision tree classifier; multiple criterion; Science and humanities

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

C, Y. (2015). Effective multiple criterion approach for building a rule based decision tree classifier;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/49373

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

C, Yamini. “Effective multiple criterion approach for building a rule based decision tree classifier;.” 2015. Thesis, Anna University. Accessed January 22, 2021. http://shodhganga.inflibnet.ac.in/handle/10603/49373.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

C, Yamini. “Effective multiple criterion approach for building a rule based decision tree classifier;.” 2015. Web. 22 Jan 2021.

Vancouver:

C Y. Effective multiple criterion approach for building a rule based decision tree classifier;. [Internet] [Thesis]. Anna University; 2015. [cited 2021 Jan 22]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/49373.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

C Y. Effective multiple criterion approach for building a rule based decision tree classifier;. [Thesis]. Anna University; 2015. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/49373

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Anna University

22. Prakash kumar S. Effective performance of integrated K family clusters and decisi on tree Structures on quality assessment of Institutional data;.

Degree: Effective performance of integrated K family clusters and decisi on tree Structures on quality assessment of Institutional data, 2015, Anna University

URL: http://shodhganga.inflibnet.ac.in/handle/10603/38937

►

The dissertation titled Effective Performance of Integrated K family newlineClusters and Decision Tree Structures on Quality Assessment of Institutional newlineData focuses primarily on the demand… (more)

▼

The dissertation titled Effective Performance of Integrated K family newlineClusters and Decision Tree Structures on Quality Assessment of Institutional newlineData focuses primarily on the demand for data mining in educational newlineInstitutions which is constantly going up due to the development of newlineinformation systems in this age of globalization The quality of data in newlineeducational institutions has not only immense influence but also plays a key newlinerole in technology newlineBy analyzing the reasons of low data quality on System Engineering newlineTheory a new method called data mining has been established which solves newlinethe data quality problem by a meta synthesis method that includes software newlinedesigning management and data mining, testing etc Its application shows newlinethat it has good practicality which can increase the institution s decision newlinelevels However the main objective of educational institution is to impart newlinequality education One way to reach the highest level of quality in education newlinesystems is by improving the decision making processes such as assessment newlineevaluation counseling and so on Data mining absolutely needs high quality newlinedata because no sufficient method is available to get quality data in the newlineinstitutional zone and therefore data mining and fuzzy based approach can newlinebe applied to find relationships between the attributes of student and staff and newlineget a conclusion Of course the growth of educational and institutional newlinesystems depends upon the quality of services under critical circumstances newlineThe faculty profile student performance and infrastructure requirements are newlineinstitutional performance Upon the decision making procedures such as newlineplanning counseling assessment evaluation and conformation the highest newlinelevel of quality can be attained Above all this can be achieved and utilized newlineby means of managerial and succinct decisions based upon implicit newlineknowledge The knowledge that remains hidden in the educational data set newlineand it can be extracted from data mining technology newline newline

appendix p192-196, reference p197-204.

Advisors/Committee Members: Sramaswami K.

Subjects/Keywords: Clusters and Decision Tree; Data mining; Quality Assessment

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

S, P. k. (2015). Effective performance of integrated K family clusters and decisi on tree Structures on quality assessment of Institutional data;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/38937

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

S, Prakash kumar. “Effective performance of integrated K family clusters and decisi on tree Structures on quality assessment of Institutional data;.” 2015. Thesis, Anna University. Accessed January 22, 2021. http://shodhganga.inflibnet.ac.in/handle/10603/38937.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

S, Prakash kumar. “Effective performance of integrated K family clusters and decisi on tree Structures on quality assessment of Institutional data;.” 2015. Web. 22 Jan 2021.

Vancouver:

S Pk. Effective performance of integrated K family clusters and decisi on tree Structures on quality assessment of Institutional data;. [Internet] [Thesis]. Anna University; 2015. [cited 2021 Jan 22]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/38937.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

S Pk. Effective performance of integrated K family clusters and decisi on tree Structures on quality assessment of Institutional data;. [Thesis]. Anna University; 2015. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/38937

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Saskatchewan

23. An, Wenyi. Decision Trees for Dynamic Decision Making And System Dynamics Modelling Calibration and Expansion.

Degree: 2014, University of Saskatchewan

URL: http://hdl.handle.net/10388/ETD-2014-06-1649

► Many practical problems raise the challenge of making decisions over time in the presence of both dynamic complexity and pronounced uncertainty regarding evolution of important… (more)

Subjects/Keywords: Computer; Decision Tree; System Dynamics; Agent-based modeling

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APA (6^th Edition):

An, W. (2014). Decision Trees for Dynamic Decision Making And System Dynamics Modelling Calibration and Expansion. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/ETD-2014-06-1649

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

An, Wenyi. “Decision Trees for Dynamic Decision Making And System Dynamics Modelling Calibration and Expansion.” 2014. Thesis, University of Saskatchewan. Accessed January 22, 2021. http://hdl.handle.net/10388/ETD-2014-06-1649.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

An, Wenyi. “Decision Trees for Dynamic Decision Making And System Dynamics Modelling Calibration and Expansion.” 2014. Web. 22 Jan 2021.

Vancouver:

An W. Decision Trees for Dynamic Decision Making And System Dynamics Modelling Calibration and Expansion. [Internet] [Thesis]. University of Saskatchewan; 2014. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10388/ETD-2014-06-1649.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

An W. Decision Trees for Dynamic Decision Making And System Dynamics Modelling Calibration and Expansion. [Thesis]. University of Saskatchewan; 2014. Available from: http://hdl.handle.net/10388/ETD-2014-06-1649

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Universiteit Utrecht

24. Berg, H. van den. The development and evaluation of a guiding system for quality improvement of pressure ulcer care.

Degree: 2015, Universiteit Utrecht

URL: http://dspace.library.uu.nl:8080/handle/1874/321304

► Title:The development and evaluation of a guiding system for quality improvement of pressure ulcer care Background: Pressure ulcers are a painful and frequently avoidable care… (more)

▼ Title:The development and evaluation of a guiding system for quality improvement of pressure ulcer care Background: Pressure ulcers are a painful and frequently avoidable care problem with high health care costs. The National Prevalence Measurement of Care Problems is an annual measurement on prevalence of several care problems, like pressure ulcers. Health care professionals struggle translating outcomes of this measurement into actions. In this study a decision tree for pressure ulcer care with action tables will be developed to assist these professionals, since a previous developed decision tree for malnutrition was received positively. Aim and research question(s) The purpose of this study is to develop a guiding system for pressure ulcer care that is suitable for managers and quality employees in hospitals, home care and long-term care settings to improve the quality of pressure ulcer care. Two research questions were formulated in succession: 1)Which elements need to be included in a guiding system, existing of a decision tree and action tables, for quality improvement of pressure ulcer care? 2)Is the developed system useful for managers and quality employees in hospitals, home care and long-term care settings to improve the quality of pressure ulcer care in their institutions? Method A mixed method was used in this study. The development phase consisted of conducting the concept decision tree and five expert interviews. In the evaluation phase a questionnaire was sent to 30 coordinators of participants of the National Prevalence Measurement of Care Problems to determine their opinion, ten of them fulfilled it. Questions about usability, clarity and completeness were in the questionnaire. Results: Coordinators evaluated this system as useful, complete and clear. Conclusion: The developed guiding system was rated as useful by the coordinators of joining institutions of the National Prevalence Measurement of Care Problems. Recommendations: Further research is required over a longer period. A longitudinal research is necessary to measure the effects on pressure ulcer care. Advisors/Committee Members: Gamel, C..

Subjects/Keywords: pressure ulcer care; decision tree; quality improvement; prevention; treatment

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APA (6^th Edition):

Berg, H. v. d. (2015). The development and evaluation of a guiding system for quality improvement of pressure ulcer care. (Masters Thesis). Universiteit Utrecht. Retrieved from http://dspace.library.uu.nl:8080/handle/1874/321304

Chicago Manual of Style (16^th Edition):

Berg, H van den. “The development and evaluation of a guiding system for quality improvement of pressure ulcer care.” 2015. Masters Thesis, Universiteit Utrecht. Accessed January 22, 2021. http://dspace.library.uu.nl:8080/handle/1874/321304.

MLA Handbook (7^th Edition):

Berg, H van den. “The development and evaluation of a guiding system for quality improvement of pressure ulcer care.” 2015. Web. 22 Jan 2021.

Vancouver:

Berg Hvd. The development and evaluation of a guiding system for quality improvement of pressure ulcer care. [Internet] [Masters thesis]. Universiteit Utrecht; 2015. [cited 2021 Jan 22]. Available from: http://dspace.library.uu.nl:8080/handle/1874/321304.

Council of Science Editors:

Berg Hvd. The development and evaluation of a guiding system for quality improvement of pressure ulcer care. [Masters Thesis]. Universiteit Utrecht; 2015. Available from: http://dspace.library.uu.nl:8080/handle/1874/321304

Addis Ababa University

25. ABEL, DAMTEW. DESIGNING A PREDICTIVE MODEL FOR HEART DISEASE DETECTION USING DATA MINING TECHNIQUES .

Degree: 2012, Addis Ababa University

URL: http://etd.aau.edu.et/dspace/handle/123456789/2766

► Background: Most countries face high and increasing rates of heart disease or Cardiovascular Disease. Even though, modern medicine is generating huge amount of data every… (more)

Subjects/Keywords: KDD; Data Mining; Decision Tree; Neural Network; Bayesian classifier; Heart Disease

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APA (6^th Edition):

ABEL, D. (2012). DESIGNING A PREDICTIVE MODEL FOR HEART DISEASE DETECTION USING DATA MINING TECHNIQUES . (Thesis). Addis Ababa University. Retrieved from http://etd.aau.edu.et/dspace/handle/123456789/2766

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

ABEL, DAMTEW. “DESIGNING A PREDICTIVE MODEL FOR HEART DISEASE DETECTION USING DATA MINING TECHNIQUES .” 2012. Thesis, Addis Ababa University. Accessed January 22, 2021. http://etd.aau.edu.et/dspace/handle/123456789/2766.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

ABEL, DAMTEW. “DESIGNING A PREDICTIVE MODEL FOR HEART DISEASE DETECTION USING DATA MINING TECHNIQUES .” 2012. Web. 22 Jan 2021.

Vancouver:

ABEL D. DESIGNING A PREDICTIVE MODEL FOR HEART DISEASE DETECTION USING DATA MINING TECHNIQUES . [Internet] [Thesis]. Addis Ababa University; 2012. [cited 2021 Jan 22]. Available from: http://etd.aau.edu.et/dspace/handle/123456789/2766.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

ABEL D. DESIGNING A PREDICTIVE MODEL FOR HEART DISEASE DETECTION USING DATA MINING TECHNIQUES . [Thesis]. Addis Ababa University; 2012. Available from: http://etd.aau.edu.et/dspace/handle/123456789/2766

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Addis Ababa University

26. TESFAHUN, HAILEMARIAM. APPLICATION OF DATA MINING FOR PREDICTING ADULT MORTALITY .

Degree: 2013, Addis Ababa University

URL: http://etd.aau.edu.et/dspace/handle/123456789/2768

► Background: The fast-growing, tremendous amount of data, collected and stored in large and massive data repositories, has far exceeded human ability for comprehension without powerful… (more)

▼ Background: The fast-growing, tremendous amount of data, collected and stored in large and massive data repositories, has far exceeded human ability for comprehension without powerful tools. As a result, data collected in large data repositories become seldom visited. This in turn, calls the application of data mining technology. Every year, more than 7·7 million children die before their fifth birthday. However, over three times those of nearly 24 million adults die every year. Less attention has been given to adults which are the most productive phase of life for both economic and social ramification of families and countries. Objective: The general objective of this research is to construct adult mortality predictive model using data mining techniques so as to identify and improve adult health status using BRHP open cohort database. Methods: The hybrid model that was developed for academic research was followed. Dataset is preprocessed for missing values, outliers and data transformation. Decision tree and Naïve Bayes algorithms were employed to build the predictive model by using a sample dataset of 62,869 records of both alive and died adults through three experiments and six scenarios. Result: In this study as compared to Bayes, the performance of J48 pruned decision tree reveals that 97.2% of accurate results are possible for developing classification rules that can be used for prediction. If no education in family and the person is living in rural highland and lowland, the probability of experiencing adult death is 98.4% and 97.4% respectively with concomitant attributes in the rule generated. The likely chance of adult to survive in completed primary school, completed secondary school, and further education is (98.9%, 99%, 100%) respectively. Conclusion: The study suggests that education plays a considerable role as a root cause of adult death, followed by outmigration. Further comprehensive and extensive experimentation is needed to substantially describe the loss experiences of adult mortality in Ethiopia. Advisors/Committee Members: Dr. Million Meshesha (advisor).

Subjects/Keywords: BRHP data; Mortality; Adult; predictive model; J48 decision tree; Data Mining.

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

TESFAHUN, H. (2013). APPLICATION OF DATA MINING FOR PREDICTING ADULT MORTALITY . (Thesis). Addis Ababa University. Retrieved from http://etd.aau.edu.et/dspace/handle/123456789/2768

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

TESFAHUN, HAILEMARIAM. “APPLICATION OF DATA MINING FOR PREDICTING ADULT MORTALITY .” 2013. Thesis, Addis Ababa University. Accessed January 22, 2021. http://etd.aau.edu.et/dspace/handle/123456789/2768.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

TESFAHUN, HAILEMARIAM. “APPLICATION OF DATA MINING FOR PREDICTING ADULT MORTALITY .” 2013. Web. 22 Jan 2021.

Vancouver:

TESFAHUN H. APPLICATION OF DATA MINING FOR PREDICTING ADULT MORTALITY . [Internet] [Thesis]. Addis Ababa University; 2013. [cited 2021 Jan 22]. Available from: http://etd.aau.edu.et/dspace/handle/123456789/2768.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

TESFAHUN H. APPLICATION OF DATA MINING FOR PREDICTING ADULT MORTALITY . [Thesis]. Addis Ababa University; 2013. Available from: http://etd.aau.edu.et/dspace/handle/123456789/2768

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

NSYSU

27. Li, Chia-En. Efficient Algorithms for Data Classification toward Knowledge Discovery based on Statistics and Decision Trees.

Degree: PhD, Computer Science and Engineering, 2018, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0630118-172505

► Knowledge discovery in the database focuses upon methodologies for extracting useful information from collection of data. One of approaches for knowledge discovery is data mining.… (more)

▼ Knowledge discovery in the database focuses upon methodologies for extracting useful information from collection of data. One of approaches for knowledge discovery is data mining. Data classification is one of famous and useful techniques for data mining that assigns categories to collected data in order to analyze the accurate prediction. Moreover, one of models for data classification is a decision tree. In fact, one of key points of a good decision tree is the kind of deciding factors in the internal nodes. In statistical tests, the chi-square test is one of good ways to analyze whether categorical variable A is the significant factor to categorical variable B. From our observation from research papers in the topic of medicine, we consider that the risk factor (i.e., the significant factor of the chi-square in statistics) is strongly related to the important deciding factor in the decision tree. Therefore, in this dissertation, first, we study the chronic kidney disease as an important risk factor for the bladder cancer by cooperating with Department of Urology, Chang Gung Memorial Hospital, Kaohsiung, Taiwan, and we propose a statistic approach to check the relation. In such a study, we need several preprocessing steps of knowledge discovery, including data selection, cleaning unclear data, and data enrichment. Moreover, the resulting risk factor (i.e., the significant factor) can be used as a deciding factor in a decision tree. Second, we make use of the significant factor to improve the performance of the decision tree, and we propose an approach which aims to reduce the number of deciding factors and decide the order of deciding factors in a decision tree. In such a study, we take the public baseball database as an example to illustrate our method. In fact, what we care about is the comparison of the performance of the same decision tree algorithm with or without using the preprocessing step, i.e., the pruning process of insignificant factors, before we construct the decision tree. Therefore, we compare the performance of the case that it uses the preprocessing step and the case that it does not use the preprocessing step. Overall, our proposed method can be applied to any other database for an extra attribute with a class value. Third, the result of mining periodicity patterns can also be helpful in knowledge discovery, and we propose a time-position join method based on a matrix and a graph for periodicity mining. In such a study, we make a comparison with the suffix tree approach proposed by Rasheed et al. For each of those three directions for research, we have shown that our contribution in terms of high accuracy, short processing time and less storage to some degree. Consequently, in this dissertation, we have proposed efficient algorithms for data classification toward knowledge discovery based on statistics and decision trees. Advisors/Committee Members: San-Yih Hwang (chair), Chiou-Shann Fuh (chair), Wei-Kuang Lai (chair), Yu-Chee Tseng (chair), Chun-I Fan (chair), Ye-In Chang (committee member), Arbee L. P. Chen (chair).

Subjects/Keywords: Periodicity Mining; Knowledge Discovery; Decision Tree; Data Classification; Chi-Square Test

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Li, C. (2018). Efficient Algorithms for Data Classification toward Knowledge Discovery based on Statistics and Decision Trees. (Doctoral Dissertation). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0630118-172505

Chicago Manual of Style (16^th Edition):

Li, Chia-En. “Efficient Algorithms for Data Classification toward Knowledge Discovery based on Statistics and Decision Trees.” 2018. Doctoral Dissertation, NSYSU. Accessed January 22, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0630118-172505.

MLA Handbook (7^th Edition):

Li, Chia-En. “Efficient Algorithms for Data Classification toward Knowledge Discovery based on Statistics and Decision Trees.” 2018. Web. 22 Jan 2021.

Vancouver:

Li C. Efficient Algorithms for Data Classification toward Knowledge Discovery based on Statistics and Decision Trees. [Internet] [Doctoral dissertation]. NSYSU; 2018. [cited 2021 Jan 22]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0630118-172505.

Council of Science Editors:

Li C. Efficient Algorithms for Data Classification toward Knowledge Discovery based on Statistics and Decision Trees. [Doctoral Dissertation]. NSYSU; 2018. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0630118-172505

University of Wollongong

28. Sun, Chao. A universal event-group based time series data mining framework for multi-variate time series classification.

Degree: PhD, 2016, University of Wollongong

URL: 0801 ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING, 0804 DATA FORMAT, 0806 INFORMATION SYSTEMS ; https://ro.uow.edu.au/theses/4682

► The Time Series Data Mining (TSDM) is an active research field due to the massive demands from industrial and other real-world practices. This thesis… (more)

Subjects/Keywords: time series data mining; event group based classifier; decision tree modelling

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APA (6^th Edition):

Sun, C. (2016). A universal event-group based time series data mining framework for multi-variate time series classification. (Doctoral Dissertation). University of Wollongong. Retrieved from 0801 ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING, 0804 DATA FORMAT, 0806 INFORMATION SYSTEMS ; https://ro.uow.edu.au/theses/4682

Chicago Manual of Style (16^th Edition):

Sun, Chao. “A universal event-group based time series data mining framework for multi-variate time series classification.” 2016. Doctoral Dissertation, University of Wollongong. Accessed January 22, 2021. 0801 ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING, 0804 DATA FORMAT, 0806 INFORMATION SYSTEMS ; https://ro.uow.edu.au/theses/4682.

MLA Handbook (7^th Edition):

Sun, Chao. “A universal event-group based time series data mining framework for multi-variate time series classification.” 2016. Web. 22 Jan 2021.

Vancouver:

Sun C. A universal event-group based time series data mining framework for multi-variate time series classification. [Internet] [Doctoral dissertation]. University of Wollongong; 2016. [cited 2021 Jan 22]. Available from: 0801 ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING, 0804 DATA FORMAT, 0806 INFORMATION SYSTEMS ; https://ro.uow.edu.au/theses/4682.

Council of Science Editors:

Sun C. A universal event-group based time series data mining framework for multi-variate time series classification. [Doctoral Dissertation]. University of Wollongong; 2016. Available from: 0801 ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING, 0804 DATA FORMAT, 0806 INFORMATION SYSTEMS ; https://ro.uow.edu.au/theses/4682

Washington State University

29. [No author]. DECISION SUPPORT FOR SUPPLIER SELECTION AND HOTEL REVENUE MANAGEMENT .

Degree: 2019, Washington State University

URL: http://hdl.handle.net/2376/16786

► This dissertation focuses on the general theme of decision support for the area of hotel revenue management (RM), as well as supply chain management. In… (more)

Subjects/Keywords: Business administration; decision tree; revenue management sophistication; structural equation; supplier selection

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APA (6^th Edition):

author], [. (2019). DECISION SUPPORT FOR SUPPLIER SELECTION AND HOTEL REVENUE MANAGEMENT . (Thesis). Washington State University. Retrieved from http://hdl.handle.net/2376/16786

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

author], [No. “DECISION SUPPORT FOR SUPPLIER SELECTION AND HOTEL REVENUE MANAGEMENT .” 2019. Thesis, Washington State University. Accessed January 22, 2021. http://hdl.handle.net/2376/16786.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

author], [No. “DECISION SUPPORT FOR SUPPLIER SELECTION AND HOTEL REVENUE MANAGEMENT .” 2019. Web. 22 Jan 2021.

Vancouver:

author] [. DECISION SUPPORT FOR SUPPLIER SELECTION AND HOTEL REVENUE MANAGEMENT . [Internet] [Thesis]. Washington State University; 2019. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/2376/16786.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

author] [. DECISION SUPPORT FOR SUPPLIER SELECTION AND HOTEL REVENUE MANAGEMENT . [Thesis]. Washington State University; 2019. Available from: http://hdl.handle.net/2376/16786

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Georgia Tech

30. Al-Hussaini, Irfan. Interpretable models for automatic sleep stage scoring.

Degree: MS, Electrical and Computer Engineering, 2020, Georgia Tech

URL: http://hdl.handle.net/1853/62851

► This thesis aims to combine domain knowledge with deep learning to develop interpretable yet robust models for a particular clinical decision support system, sleep staging.… (more)

Subjects/Keywords: Sleep scoring; Interpretable; Deep learning; CNN; Decision tree; EEG; EOG; EMG

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APA (6^th Edition):

Al-Hussaini, I. (2020). Interpretable models for automatic sleep stage scoring. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62851

Chicago Manual of Style (16^th Edition):

Al-Hussaini, Irfan. “Interpretable models for automatic sleep stage scoring.” 2020. Masters Thesis, Georgia Tech. Accessed January 22, 2021. http://hdl.handle.net/1853/62851.

MLA Handbook (7^th Edition):

Al-Hussaini, Irfan. “Interpretable models for automatic sleep stage scoring.” 2020. Web. 22 Jan 2021.

Vancouver:

Al-Hussaini I. Interpretable models for automatic sleep stage scoring. [Internet] [Masters thesis]. Georgia Tech; 2020. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/1853/62851.

Council of Science Editors:

Al-Hussaini I. Interpretable models for automatic sleep stage scoring. [Masters Thesis]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/62851

Open Access Theses and Dissertations