subject:( Naive Bayes classifier)

1. Vallin, Simon. Likelihood-based classification of single trees in hemi-boreal forests.

Degree: Mathematics and Mathematical Statistics, 2015, Umeå University

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-99691

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Determining species of individual trees is important for forest management. In this thesis we investigate if it is possible to discriminate between Norway spruce,… (more)

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Determining species of individual trees is important for forest management. In this thesis we investigate if it is possible to discriminate between Norway spruce, Scots pine and deciduous trees from airborne laser scanning data by using unique probability density functions estimated for each specie. We estimate the probability density functions in three different ways: by fitting a beta distribution, histogram density estimation and kernel density estimation. All these methods classifies single laser returns (and not segments of laser returns). The resulting classification is compared with a reference method based on features extracted from airborne laser scanning data.We measure how well a method performs by using the overall accuracy, that is the proportion of correctly predicted trees. The highest overall accuracy obtained by the methods we developed in this thesis is obtained by using histogram-density estimation where an overall accuracy of 83.4 percent is achieved. This result can be compared with the best result from the reference method that produced an overall accuracy of 84.1 percent. The fact that we achieve a high level of correctly classified trees indicates that it is possible to use these types of methods for identification of tree species.

Att kunna artbestämma enskilda träd är viktigt inom skogsbruket. I denna uppsats undersöker vi om det är möjligt att skilja mellan gran, tall och lövträd med data från en flygburen laserskanner genom att skatta en unik täthetsfunktion för varje trädslag. Täthetsfunktionerna skattas på tre olika sätt: genom att anpassa en beta-fördelning, skatta täthetsfunktionen med histogram samt skatta täthetsfunktionen med en kernel täthetsskattning. Alla dessa metoder klassificerar varje enskild laserretur (och inte segment av laserreturer). Resultaten från vår klassificering jämförs sedan med en referensmetod som bygger på särdrag från laserskanner data. Vi mäter hur väl metoderna presterar genom att jämföra den totala precisionen, vilket är andelen korrektklassificerade träd. Den högsta totala precisionen för de framtagna metoderna i denna uppsats erhölls med metoden som bygger på täthetsskattning med histogram. Precisionen för denna metod var 83,4 procent rättklassicerade träd. Detta kan jämföras med en rättklassificering på 84,1 procent vilket är det bästa resultatet för referensmetoderna. Att vi erhåller en så pass hög grad av rättklassificerade träd tyder på att de metoder som vi använder oss av är användbara för trädslagsklassificering.

Subjects/Keywords: Classification of single trees; likelihood-based classification; naive bayes classifier

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APA (6^th Edition):

Vallin, S. (2015). Likelihood-based classification of single trees in hemi-boreal forests. (Thesis). Umeå University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-99691

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):

Vallin, Simon. “Likelihood-based classification of single trees in hemi-boreal forests.” 2015. Thesis, Umeå University. Accessed January 17, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-99691.

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

MLA Handbook (7^th Edition):

Vallin, Simon. “Likelihood-based classification of single trees in hemi-boreal forests.” 2015. Web. 17 Jan 2021.

Vancouver:

Vallin S. Likelihood-based classification of single trees in hemi-boreal forests. [Internet] [Thesis]. Umeå University; 2015. [cited 2021 Jan 17]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-99691.

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

Council of Science Editors:

Vallin S. Likelihood-based classification of single trees in hemi-boreal forests. [Thesis]. Umeå University; 2015. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-99691

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

2. SILVA, Antonio Carlos de Castro da. Reconhecimento automático de defeitos de fabricação em painéis TFT-LCD através de inspeção de imagem .

Degree: 2016, Universidade Federal de Pernambuco

URL: http://repositorio.ufpe.br/handle/123456789/17823

► A detecção prematura de defeitos nos componentes de linhas de montagem de fabricação é determinante para a obtenção de produtos finais de boa qualidade. Partindo… (more)

Subjects/Keywords: TFT-LCD; plataforma; reconhecimento de imagem; detecção automática; classificador Naive Bayes; TFT-LCD; platform; image recognition; automatic detection; Naive Bayes classifier

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APA (6^th Edition):

SILVA, A. C. d. C. d. (2016). Reconhecimento automático de defeitos de fabricação em painéis TFT-LCD através de inspeção de imagem . (Thesis). Universidade Federal de Pernambuco. Retrieved from http://repositorio.ufpe.br/handle/123456789/17823

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):

SILVA, Antonio Carlos de Castro da. “Reconhecimento automático de defeitos de fabricação em painéis TFT-LCD através de inspeção de imagem .” 2016. Thesis, Universidade Federal de Pernambuco. Accessed January 17, 2021. http://repositorio.ufpe.br/handle/123456789/17823.

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

MLA Handbook (7^th Edition):

SILVA, Antonio Carlos de Castro da. “Reconhecimento automático de defeitos de fabricação em painéis TFT-LCD através de inspeção de imagem .” 2016. Web. 17 Jan 2021.

Vancouver:

SILVA ACdCd. Reconhecimento automático de defeitos de fabricação em painéis TFT-LCD através de inspeção de imagem . [Internet] [Thesis]. Universidade Federal de Pernambuco; 2016. [cited 2021 Jan 17]. Available from: http://repositorio.ufpe.br/handle/123456789/17823.

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

Council of Science Editors:

SILVA ACdCd. Reconhecimento automático de defeitos de fabricação em painéis TFT-LCD através de inspeção de imagem . [Thesis]. Universidade Federal de Pernambuco; 2016. Available from: http://repositorio.ufpe.br/handle/123456789/17823

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

NSYSU

3. Lai, Hsiang-Erh. Big Data Analytics Platform Establishment: Efficiency Analysis and Spam Email Filtering.

Degree: Master, Electrical Engineering, 2015, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0830115-201456

► The era of big data has come. Except for the profit, big data brings more challenges for data analysis. Thus, the Hadoop platform is proposed… (more)

Subjects/Keywords: TF-IDF; naive Bayes classifier; distributed computing; spam email filtering; Hadoop; big data

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APA (6^th Edition):

Lai, H. (2015). Big Data Analytics Platform Establishment: Efficiency Analysis and Spam Email Filtering. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0830115-201456

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):

Lai, Hsiang-Erh. “Big Data Analytics Platform Establishment: Efficiency Analysis and Spam Email Filtering.” 2015. Thesis, NSYSU. Accessed January 17, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0830115-201456.

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

MLA Handbook (7^th Edition):

Lai, Hsiang-Erh. “Big Data Analytics Platform Establishment: Efficiency Analysis and Spam Email Filtering.” 2015. Web. 17 Jan 2021.

Vancouver:

Lai H. Big Data Analytics Platform Establishment: Efficiency Analysis and Spam Email Filtering. [Internet] [Thesis]. NSYSU; 2015. [cited 2021 Jan 17]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0830115-201456.

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

Council of Science Editors:

Lai H. Big Data Analytics Platform Establishment: Efficiency Analysis and Spam Email Filtering. [Thesis]. NSYSU; 2015. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0830115-201456

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

4. Kavitha G. Assessment and classification of Retinal images using ant colony Optimization based hybrid methods And support vector machines;.

Degree: Assessment and classification of Retinal images using ant colony Optimization based hybrid methods And support vector machines, 2014, Anna University

URL: http://shodhganga.inflibnet.ac.in/handle/10603/30842

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In this work digital retinal images in health and diseases have been newlineanalysed using Optimization based algorithm and hybrid techniques The newlineacquired fundus images N… (more)

Subjects/Keywords: Ant Colony Optimization; Naive Bayes classifier; Positive Predictive Value; Receiver Operating Characteristics; Support Vector Machines

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APA (6^th Edition):

G, K. (2014). Assessment and classification of Retinal images using ant colony Optimization based hybrid methods And support vector machines;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/30842

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):

G, Kavitha. “Assessment and classification of Retinal images using ant colony Optimization based hybrid methods And support vector machines;.” 2014. Thesis, Anna University. Accessed January 17, 2021. http://shodhganga.inflibnet.ac.in/handle/10603/30842.

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

MLA Handbook (7^th Edition):

G, Kavitha. “Assessment and classification of Retinal images using ant colony Optimization based hybrid methods And support vector machines;.” 2014. Web. 17 Jan 2021.

Vancouver:

G K. Assessment and classification of Retinal images using ant colony Optimization based hybrid methods And support vector machines;. [Internet] [Thesis]. Anna University; 2014. [cited 2021 Jan 17]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/30842.

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

Council of Science Editors:

G K. Assessment and classification of Retinal images using ant colony Optimization based hybrid methods And support vector machines;. [Thesis]. Anna University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/30842

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

University of Saskatchewan

5. Oraji, Rahim. A Machine Learning Generalization of LSI-OR.

Degree: 2016, University of Saskatchewan

URL: http://hdl.handle.net/10388/7318

► The Level of Service Inventory-Ontario Revision (LSI-OR) is used as a risk/need assessment tool to classify, manage, and treat the offender population so that they… (more)

▼ The Level of Service Inventory-Ontario Revision (LSI-OR) is used as a risk/need assessment tool to classify, manage, and treat the offender population so that they receive supportive services consistent with their custodial needs. This thesis adopts a machine learning approach employing the Naive Bayes technique as an alternative to the LSI-OR. The study was conducted on a group of (72725) offenders with different races and includes males (82.62%) and females (17.38%). Participants were monitored for two years to collect recidivism information. A basic analysis of the dataset revealed that 1) 83.18% of population used a unique pattern to answer 43 LSI-OR items, 2) the total LSI-OR scores in the entire population and also in male and female population followed two beta distribution functions, one for each recidivism class, and 3) the recidivism rate was approximated by a normal distribution function. It was shown that the Naive Bayes classifier can be considered as an extended LSI-OR classifier that accepts multiple continuous and discrete features as input. In other words, the Naive Bayes classifier provides a simple framework for studying the effect of distinct features on classification efficiency and accuracy. The results of running the Naive Bayes classifier with various input features revealed that the Naive Bayes classifier presented better performance than the LSI-OR. However, there was no obvious trend in the accuracies predicted by both models to indicate the superiority of one model over the other. The only feature whose value could be treated as a continuous variable was the LSI-OR score. Many models were created based on continuous and discrete LSI-OR scores producing either the same performance and mean accuracy or slightly better. The dataset contained many features that are never used by the LSI-OR assessment for instance, the offence severity. A model was built at each index of offence severity based on LSI-OR scores and 43 LSI-OR items as input features. The results of running the experiment indicate that considering 43 LSI-OR items gives more stable results in terms of accuracy than the LSI-OR scores. Advisors/Committee Members: Spiteri, Raymond, Eramian, Mark, Stanley, Kevin, Mago, Vijay.

Subjects/Keywords: LSI-OR; Naive Bayes; machine learning; level of service inventory; classifier; algorithm

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

APA (6^th Edition):

Oraji, R. (2016). A Machine Learning Generalization of LSI-OR. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/7318

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):

Oraji, Rahim. “A Machine Learning Generalization of LSI-OR.” 2016. Thesis, University of Saskatchewan. Accessed January 17, 2021. http://hdl.handle.net/10388/7318.

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

MLA Handbook (7^th Edition):

Oraji, Rahim. “A Machine Learning Generalization of LSI-OR.” 2016. Web. 17 Jan 2021.

Vancouver:

Oraji R. A Machine Learning Generalization of LSI-OR. [Internet] [Thesis]. University of Saskatchewan; 2016. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10388/7318.

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

Council of Science Editors:

Oraji R. A Machine Learning Generalization of LSI-OR. [Thesis]. University of Saskatchewan; 2016. Available from: http://hdl.handle.net/10388/7318

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

6. Pyon, Yoon Soo. Variant Detection Using Next Generation Sequencing Data.

Degree: PhD, EECS - Computer and Information Sciences, 2013, Case Western Reserve University School of Graduate Studies

URL: http://rave.ohiolink.edu/etdc/view?acc_num=case1347053645

► Genetic variants, including single nucleotide polymorphisms (SNPs) and genomic structural variations (SVs), not only contribute to human diversity, but also are important to human health… (more)

Subjects/Keywords: Bioinformatics; Computer Science; Genetics; structural variation; SNP; next generation sequencing; naive Bayes classifier

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APA (6^th Edition):

Pyon, Y. S. (2013). Variant Detection Using Next Generation Sequencing Data. (Doctoral Dissertation). Case Western Reserve University School of Graduate Studies. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=case1347053645

Chicago Manual of Style (16^th Edition):

Pyon, Yoon Soo. “Variant Detection Using Next Generation Sequencing Data.” 2013. Doctoral Dissertation, Case Western Reserve University School of Graduate Studies. Accessed January 17, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=case1347053645.

MLA Handbook (7^th Edition):

Pyon, Yoon Soo. “Variant Detection Using Next Generation Sequencing Data.” 2013. Web. 17 Jan 2021.

Vancouver:

Pyon YS. Variant Detection Using Next Generation Sequencing Data. [Internet] [Doctoral dissertation]. Case Western Reserve University School of Graduate Studies; 2013. [cited 2021 Jan 17]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1347053645.

Council of Science Editors:

Pyon YS. Variant Detection Using Next Generation Sequencing Data. [Doctoral Dissertation]. Case Western Reserve University School of Graduate Studies; 2013. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1347053645

Brigham Young University

7. Lee, Jun won. Relationships Among Learning Algorithms and Tasks.

Degree: PhD, 2011, Brigham Young University

URL: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=3477&context=etd

► Metalearning aims to obtain knowledge of the relationship between the mechanism of learning and the concrete contexts in which that mechanisms is applicable. As new… (more)

Subjects/Keywords: MetaLearning; Classifier Output Difference; Naive Bayes; radial basis function; network; clustering; algorithm selection model; Computer Sciences

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APA (6^th Edition):

Lee, J. w. (2011). Relationships Among Learning Algorithms and Tasks. (Doctoral Dissertation). Brigham Young University. Retrieved from https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=3477&context=etd

Chicago Manual of Style (16^th Edition):

Lee, Jun won. “Relationships Among Learning Algorithms and Tasks.” 2011. Doctoral Dissertation, Brigham Young University. Accessed January 17, 2021. https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=3477&context=etd.

MLA Handbook (7^th Edition):

Lee, Jun won. “Relationships Among Learning Algorithms and Tasks.” 2011. Web. 17 Jan 2021.

Vancouver:

Lee Jw. Relationships Among Learning Algorithms and Tasks. [Internet] [Doctoral dissertation]. Brigham Young University; 2011. [cited 2021 Jan 17]. Available from: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=3477&context=etd.

Council of Science Editors:

Lee Jw. Relationships Among Learning Algorithms and Tasks. [Doctoral Dissertation]. Brigham Young University; 2011. Available from: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=3477&context=etd

Brno University of Technology

8. Krčmář, Martin. Analýza dat z výrobního procesu: Data analysis from the manufacturing process.

Degree: 2019, Brno University of Technology

URL: http://hdl.handle.net/11012/31693

► This thesis deals with the classification of production data using algorithms: neural networks, decision trees and naive bayesian classifier. The neural network is dedicated forward… (more)

Subjects/Keywords: neuronová síť; backpropagation; rozhodovací strom; naivní bayesovský klasfikátor; C#; COMES; neural network; backpropagation; decision tree; naive bayes classifier; C#; COMES

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APA (6^th Edition):

Krčmář, M. (2019). Analýza dat z výrobního procesu: Data analysis from the manufacturing process. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/31693

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):

Krčmář, Martin. “Analýza dat z výrobního procesu: Data analysis from the manufacturing process.” 2019. Thesis, Brno University of Technology. Accessed January 17, 2021. http://hdl.handle.net/11012/31693.

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

MLA Handbook (7^th Edition):

Krčmář, Martin. “Analýza dat z výrobního procesu: Data analysis from the manufacturing process.” 2019. Web. 17 Jan 2021.

Vancouver:

Krčmář M. Analýza dat z výrobního procesu: Data analysis from the manufacturing process. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/11012/31693.

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

Council of Science Editors:

Krčmář M. Analýza dat z výrobního procesu: Data analysis from the manufacturing process. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/31693

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

Brno University of Technology

9. Vodička, Jan. Metody strojového učení ve zpracování přirozeného jazyka: Machine-Learning Methods in Natural Language Processing.

Degree: 2019, Brno University of Technology

URL: http://hdl.handle.net/11012/55221

► Bachelor's thesis deals with sentiment analysis using machine learning methods, mainly naive bayes classifier. Input text can be classified as positive or negative message. There… (more)

Subjects/Keywords: Strojové učení; naivní bayesovský klasifikátor; hodnocení sentimentu; dolování názorů; Twitter; Machine learning; naive Bayes classifier; sentiment analysis; opinion mining; Twitter

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APA (6^th Edition):

Vodička, J. (2019). Metody strojového učení ve zpracování přirozeného jazyka: Machine-Learning Methods in Natural Language Processing. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/55221

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):

Vodička, Jan. “Metody strojového učení ve zpracování přirozeného jazyka: Machine-Learning Methods in Natural Language Processing.” 2019. Thesis, Brno University of Technology. Accessed January 17, 2021. http://hdl.handle.net/11012/55221.

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

MLA Handbook (7^th Edition):

Vodička, Jan. “Metody strojového učení ve zpracování přirozeného jazyka: Machine-Learning Methods in Natural Language Processing.” 2019. Web. 17 Jan 2021.

Vancouver:

Vodička J. Metody strojového učení ve zpracování přirozeného jazyka: Machine-Learning Methods in Natural Language Processing. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/11012/55221.

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

Council of Science Editors:

Vodička J. Metody strojového učení ve zpracování přirozeného jazyka: Machine-Learning Methods in Natural Language Processing. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/55221

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

Brno University of Technology

10. Molnár, Ondřej. Klasifikace dokumentů pomocí umělé inteligence: Artificial Intelligence Document Classification.

Degree: 2019, Brno University of Technology

URL: http://hdl.handle.net/11012/180209

► This paper deals with document classification using artificial intelligence. It describes the principles of classification and machine learning. It also introduces AI methods and presents… (more)

Subjects/Keywords: umělá inteligence; UI; klasifikace textu; klasifikace dokumentů; klasifikátor; naivní Bayes; strojové učení; zpracování přirozeného jazyka; Artificial intelligence; AI; Text Classification; Document classification; Classifier; Naive Bayes; Machine learning; Natural language processing

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APA (6^th Edition):

Molnár, O. (2019). Klasifikace dokumentů pomocí umělé inteligence: Artificial Intelligence Document Classification. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/180209

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):

Molnár, Ondřej. “Klasifikace dokumentů pomocí umělé inteligence: Artificial Intelligence Document Classification.” 2019. Thesis, Brno University of Technology. Accessed January 17, 2021. http://hdl.handle.net/11012/180209.

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

MLA Handbook (7^th Edition):

Molnár, Ondřej. “Klasifikace dokumentů pomocí umělé inteligence: Artificial Intelligence Document Classification.” 2019. Web. 17 Jan 2021.

Vancouver:

Molnár O. Klasifikace dokumentů pomocí umělé inteligence: Artificial Intelligence Document Classification. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/11012/180209.

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

Council of Science Editors:

Molnár O. Klasifikace dokumentů pomocí umělé inteligence: Artificial Intelligence Document Classification. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/180209

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

Oklahoma State University

11. Spain, Marc. Study on log event noise reduction by using Naive Bayes supervised machine learning.

Degree: Computer Science, 2019, Oklahoma State University

URL: http://hdl.handle.net/11244/324912

► This research addresses which Naive Bayes model would be best to predict Windows log events that could be considered noise or in other words not… (more)

Subjects/Keywords: naive bayes; supervised machine learning

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APA (6^th Edition):

Spain, M. (2019). Study on log event noise reduction by using Naive Bayes supervised machine learning. (Thesis). Oklahoma State University. Retrieved from http://hdl.handle.net/11244/324912

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):

Spain, Marc. “Study on log event noise reduction by using Naive Bayes supervised machine learning.” 2019. Thesis, Oklahoma State University. Accessed January 17, 2021. http://hdl.handle.net/11244/324912.

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

MLA Handbook (7^th Edition):

Spain, Marc. “Study on log event noise reduction by using Naive Bayes supervised machine learning.” 2019. Web. 17 Jan 2021.

Vancouver:

Spain M. Study on log event noise reduction by using Naive Bayes supervised machine learning. [Internet] [Thesis]. Oklahoma State University; 2019. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/11244/324912.

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

Council of Science Editors:

Spain M. Study on log event noise reduction by using Naive Bayes supervised machine learning. [Thesis]. Oklahoma State University; 2019. Available from: http://hdl.handle.net/11244/324912

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

University of Saskatchewan

12. Yang, Xiuxin. A wearable real-time system for physical activity recognition and fall detection.

Degree: 2010, University of Saskatchewan

URL: http://hdl.handle.net/10388/etd-09212010-164509

► This thesis work designs and implements a wearable system to recognize physical activities and detect fall in real time. Recognizing people’s physical activity has a… (more)

▼ This thesis work designs and implements a wearable system to recognize physical activities and detect fall in real time. Recognizing people’s physical activity has a broad range of applications. These include helping people maintaining their energy balance by developing health assessment and intervention tools, investigating the links between common diseases and levels of physical activity, and providing feedback to motivate individuals to exercise. In addition, fall detection has become a hot research topic due to the increasing population over 65 throughout the world, as well as the serious effects and problems caused by fall. In this work, the Sun SPOT wireless sensor system is used as the hardware platform to recognize physical activity and detect fall. The sensors with tri-axis accelerometers are used to collect acceleration data, which are further processed and extracted with useful information. The evaluation results from various algorithms indicate that Naive Bayes algorithm works better than other popular algorithms both in accuracy and implementation in this particular application. This wearable system works in two modes: indoor and outdoor, depending on user’s demand. Naive Bayes classifier is successfully implemented in the Sun SPOT sensor. The results of evaluating sampling rate denote that 20 Hz is an optimal sampling frequency in this application. If only one sensor is available to recognize physical activity, the best location is attaching it to the thigh. If two sensors are available, the combination at the left thigh and the right thigh is the best option, 90.52% overall accuracy in the experiment. For fall detection, a master sensor is attached to the chest, and a slave sensor is attached to the thigh to collect acceleration data. The results show that all falls are successfully detected. Forward, backward, leftward and rightward falls have been distinguished from standing and walking using the fall detection algorithm. Normal physical activities are not misclassified as fall, and there is no false alarm in fall detection while the user is wearing the system in daily life. Advisors/Committee Members: Chen, Li, Dinh, Anh, Ko, Seok-Bum, Wahid, Khan A., Chen, Daniel.

Subjects/Keywords: Machine learning; Accelerometer; Naive Bayes classifier; Fall detection; Physical activity recognition

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APA (6^th Edition):

Yang, X. (2010). A wearable real-time system for physical activity recognition and fall detection. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/etd-09212010-164509

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):

Yang, Xiuxin. “A wearable real-time system for physical activity recognition and fall detection.” 2010. Thesis, University of Saskatchewan. Accessed January 17, 2021. http://hdl.handle.net/10388/etd-09212010-164509.

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

MLA Handbook (7^th Edition):

Yang, Xiuxin. “A wearable real-time system for physical activity recognition and fall detection.” 2010. Web. 17 Jan 2021.

Vancouver:

Yang X. A wearable real-time system for physical activity recognition and fall detection. [Internet] [Thesis]. University of Saskatchewan; 2010. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10388/etd-09212010-164509.

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

Council of Science Editors:

Yang X. A wearable real-time system for physical activity recognition and fall detection. [Thesis]. University of Saskatchewan; 2010. Available from: http://hdl.handle.net/10388/etd-09212010-164509

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

13. Berisha, Sebastian. Image Classification using Gabor Filters and Machine Learning.

Degree: 2009, Wake Forest University

URL: http://hdl.handle.net/10339/14727

► Feature extraction and classification are important areas of research in image processing and computer vision with a myriad of applications in science and industry. The… (more)

Subjects/Keywords: image processing; image classification; Gabor filter; naive Bayes classifier; SVM

…Bayesian networks. (a) Naive Bayes classifier; (b) Bayesian classifier [… …classification purposes. A naive Bayes classifier is a simple but highly effective probabilistic… …classifier based on the application of Bayes’ theorem. A naive Bayes classifier assumes that the… …conditional probabilities from naive Bayes classifier and a mutual information feature vector are… …naive Bayes classifier. • Demonstration that binary classification of aerial imagery can be…

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APA (6^th Edition):

Berisha, S. (2009). Image Classification using Gabor Filters and Machine Learning. (Thesis). Wake Forest University. Retrieved from http://hdl.handle.net/10339/14727

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):

Berisha, Sebastian. “Image Classification using Gabor Filters and Machine Learning.” 2009. Thesis, Wake Forest University. Accessed January 17, 2021. http://hdl.handle.net/10339/14727.

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

MLA Handbook (7^th Edition):

Berisha, Sebastian. “Image Classification using Gabor Filters and Machine Learning.” 2009. Web. 17 Jan 2021.

Vancouver:

Berisha S. Image Classification using Gabor Filters and Machine Learning. [Internet] [Thesis]. Wake Forest University; 2009. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10339/14727.

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

Council of Science Editors:

Berisha S. Image Classification using Gabor Filters and Machine Learning. [Thesis]. Wake Forest University; 2009. Available from: http://hdl.handle.net/10339/14727

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

Linköping University

14. Helmersson, Benjamin. Definition Extraction From Swedish Technical Documentation : Bridging the gap between industry and academy approaches.

Degree: Computer and Information Science, 2016, Linköping University

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-131057

► Terminology is concerned with the creation and maintenance of concept systems, terms and definitions. Automatic term and definition extraction is used to simplify this… (more)

Subjects/Keywords: definition extraction; machine learning; pattern matching; naive bayes; regular expressions; rev; classifier; terminology; comparison; definitionsextraktion; maskininlärning; mönstermatchning; reguljära uttryck; rev; klassificerare; terminologi; jämförelse; Language Technology (Computational Linguistics); Språkteknologi (språkvetenskaplig databehandling)

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APA (6^th Edition):

Helmersson, B. (2016). Definition Extraction From Swedish Technical Documentation : Bridging the gap between industry and academy approaches. (Thesis). Linköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-131057

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):

Helmersson, Benjamin. “Definition Extraction From Swedish Technical Documentation : Bridging the gap between industry and academy approaches.” 2016. Thesis, Linköping University. Accessed January 17, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-131057.

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

MLA Handbook (7^th Edition):

Helmersson, Benjamin. “Definition Extraction From Swedish Technical Documentation : Bridging the gap between industry and academy approaches.” 2016. Web. 17 Jan 2021.

Vancouver:

Helmersson B. Definition Extraction From Swedish Technical Documentation : Bridging the gap between industry and academy approaches. [Internet] [Thesis]. Linköping University; 2016. [cited 2021 Jan 17]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-131057.

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

Council of Science Editors:

Helmersson B. Definition Extraction From Swedish Technical Documentation : Bridging the gap between industry and academy approaches. [Thesis]. Linköping University; 2016. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-131057

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

Brno University of Technology

15. Petřík, Patrik. Predikce vývoje akciového trhu prostřednictvím technické a psychologické analýzy: Stock Market Prediction via Technical and Psychological Analysis.

Degree: 2014, Brno University of Technology

URL: http://hdl.handle.net/11012/14452

► This work deals with stock market prediction via technical and psychological analysis. We introduce theoretical resources of technical and psychological analysis. We also introduce some… (more)

Subjects/Keywords: Predikce; technická analýza; psychologická analýza; klasifikace; naivní Bayesův klasifikátor; neuronová síť; evoluční algoritmy.; Stock market prediction; technical analysis; psychological analysis; classification; naive Bayes classifier; neural network; genetic algorithm.

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APA (6^th Edition):

Petřík, P. (2014). Predikce vývoje akciového trhu prostřednictvím technické a psychologické analýzy: Stock Market Prediction via Technical and Psychological Analysis. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/14452

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):

Petřík, Patrik. “Predikce vývoje akciového trhu prostřednictvím technické a psychologické analýzy: Stock Market Prediction via Technical and Psychological Analysis.” 2014. Thesis, Brno University of Technology. Accessed January 17, 2021. http://hdl.handle.net/11012/14452.

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

MLA Handbook (7^th Edition):

Petřík, Patrik. “Predikce vývoje akciového trhu prostřednictvím technické a psychologické analýzy: Stock Market Prediction via Technical and Psychological Analysis.” 2014. Web. 17 Jan 2021.

Vancouver:

Petřík P. Predikce vývoje akciového trhu prostřednictvím technické a psychologické analýzy: Stock Market Prediction via Technical and Psychological Analysis. [Internet] [Thesis]. Brno University of Technology; 2014. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/11012/14452.

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

Council of Science Editors:

Petřík P. Predikce vývoje akciového trhu prostřednictvím technické a psychologické analýzy: Stock Market Prediction via Technical and Psychological Analysis. [Thesis]. Brno University of Technology; 2014. Available from: http://hdl.handle.net/11012/14452

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

Brno University of Technology

16. Kraus, Michal. Zjednoznačňování slovních významů: Word Sense Disambiguation.

Degree: 2019, Brno University of Technology

URL: http://hdl.handle.net/11012/53207

► The master's thesis deals with sense disambiguation of Czech words. Reader is informed about task's history and used algorithms are introduced. There are naive Bayes… (more)

Subjects/Keywords: zpracování přirozeného jazyka; český jazyk; zjednoznačňování slovních významů; klasifikační algoritmy; naivní Bayesův klasifikátor; klasifikátor AdaBoost; metoda maximální entropie; rozhodovací stromy; natural language processing; Czech language; word sense disambiguation; classifiers; naive Bayes classifier; AdaBoost classifier; maximum entrophy method; decision trees

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APA (6^th Edition):

Kraus, M. (2019). Zjednoznačňování slovních významů: Word Sense Disambiguation. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/53207

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):

Kraus, Michal. “Zjednoznačňování slovních významů: Word Sense Disambiguation.” 2019. Thesis, Brno University of Technology. Accessed January 17, 2021. http://hdl.handle.net/11012/53207.

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

MLA Handbook (7^th Edition):

Kraus, Michal. “Zjednoznačňování slovních významů: Word Sense Disambiguation.” 2019. Web. 17 Jan 2021.

Vancouver:

Kraus M. Zjednoznačňování slovních významů: Word Sense Disambiguation. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/11012/53207.

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

Council of Science Editors:

Kraus M. Zjednoznačňování slovních významů: Word Sense Disambiguation. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/53207

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

Brno University of Technology

17. Hrach, Vlastimil. Využití prostředků umělé inteligence na kapitálových trzích: The Use of Means of Artificial Intelligence for the Decision Making Support on Stock Market.

Degree: 2019, Brno University of Technology

URL: http://hdl.handle.net/11012/6711

► The diploma thesis deals with artificial intelligence utilization for predictions on stock markets.The prediction is unconventionally based on Bayes' probabilistic model theorem and on its… (more)

Subjects/Keywords: Akcie; akciový trh; predikce; umělá inteligente; strojové učení; pravděpodobnost; hypotéza; Bayes; naivní bayesův klasifikátor; klouzavý průměr; Stock; stock market; prediction; artifical inteligence; machine learning; probability; hypothesis; Bayes; naive bayesian classifier; moving average

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APA (6^th Edition):

Hrach, V. (2019). Využití prostředků umělé inteligence na kapitálových trzích: The Use of Means of Artificial Intelligence for the Decision Making Support on Stock Market. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/6711

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):

Hrach, Vlastimil. “Využití prostředků umělé inteligence na kapitálových trzích: The Use of Means of Artificial Intelligence for the Decision Making Support on Stock Market.” 2019. Thesis, Brno University of Technology. Accessed January 17, 2021. http://hdl.handle.net/11012/6711.

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

MLA Handbook (7^th Edition):

Hrach, Vlastimil. “Využití prostředků umělé inteligence na kapitálových trzích: The Use of Means of Artificial Intelligence for the Decision Making Support on Stock Market.” 2019. Web. 17 Jan 2021.

Vancouver:

Hrach V. Využití prostředků umělé inteligence na kapitálových trzích: The Use of Means of Artificial Intelligence for the Decision Making Support on Stock Market. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/11012/6711.

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

Council of Science Editors:

Hrach V. Využití prostředků umělé inteligence na kapitálových trzích: The Use of Means of Artificial Intelligence for the Decision Making Support on Stock Market. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/6711

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

University of Edinburgh

18. Maftei, Dan. Proto-Phoneme Reconstruction as Naive Bayes Inference.

Degree: 2012, University of Edinburgh

URL: http://hdl.handle.net/1842/8593

► The comparative method is the standard technique by which historical linguists reconstruct ancestral languages from their descendants. The method, however, has received little attention from… (more)

Subjects/Keywords: linguistics; comparative method; computational linguistics; naive bayes

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APA (6^th Edition):

Maftei, D. (2012). Proto-Phoneme Reconstruction as Naive Bayes Inference. (Thesis). University of Edinburgh. Retrieved from http://hdl.handle.net/1842/8593

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):

Maftei, Dan. “Proto-Phoneme Reconstruction as Naive Bayes Inference.” 2012. Thesis, University of Edinburgh. Accessed January 17, 2021. http://hdl.handle.net/1842/8593.

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

MLA Handbook (7^th Edition):

Maftei, Dan. “Proto-Phoneme Reconstruction as Naive Bayes Inference.” 2012. Web. 17 Jan 2021.

Vancouver:

Maftei D. Proto-Phoneme Reconstruction as Naive Bayes Inference. [Internet] [Thesis]. University of Edinburgh; 2012. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/1842/8593.

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

Council of Science Editors:

Maftei D. Proto-Phoneme Reconstruction as Naive Bayes Inference. [Thesis]. University of Edinburgh; 2012. Available from: http://hdl.handle.net/1842/8593

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

KTH

19. Liu, Chang. Data Analysis of Minimally-Structured Heterogeneous Logs : An experimental study of log template extraction and anomaly detection based on Recurrent Neural Network and Naive Bayes.

Degree: Computer Science and Communication (CSC), 2016, KTH

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-191334

► Nowadays, the ideas of continuous integration and continuous delivery are under heavy usage in order to achieve rapid software development speed and quick product… (more)

Subjects/Keywords: Data analysis; Log analysis; RNN; Naive Bayes

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APA (6^th Edition):

Liu, C. (2016). Data Analysis of Minimally-Structured Heterogeneous Logs : An experimental study of log template extraction and anomaly detection based on Recurrent Neural Network and Naive Bayes. (Thesis). KTH. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-191334

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, Chang. “Data Analysis of Minimally-Structured Heterogeneous Logs : An experimental study of log template extraction and anomaly detection based on Recurrent Neural Network and Naive Bayes.” 2016. Thesis, KTH. Accessed January 17, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-191334.

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, Chang. “Data Analysis of Minimally-Structured Heterogeneous Logs : An experimental study of log template extraction and anomaly detection based on Recurrent Neural Network and Naive Bayes.” 2016. Web. 17 Jan 2021.

Vancouver:

Liu C. Data Analysis of Minimally-Structured Heterogeneous Logs : An experimental study of log template extraction and anomaly detection based on Recurrent Neural Network and Naive Bayes. [Internet] [Thesis]. KTH; 2016. [cited 2021 Jan 17]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-191334.

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

Council of Science Editors:

Liu C. Data Analysis of Minimally-Structured Heterogeneous Logs : An experimental study of log template extraction and anomaly detection based on Recurrent Neural Network and Naive Bayes. [Thesis]. KTH; 2016. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-191334

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

20. Sudheep Elayidom, M. Design and Development of data mining Models for the Prediction of Manpower Placement in the Technical Domain.

Degree: 2012, Cochin University of Science and Technology

URL: http://dyuthi.cusat.ac.in/purl/5126

Subjects/Keywords: Dataset; Data mining; Data mining models; Neural networks; Data pre-processing; Neural networks; Naive Bayes classifier

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APA (6^th Edition):

Sudheep Elayidom, M. (2012). Design and Development of data mining Models for the Prediction of Manpower Placement in the Technical Domain. (Thesis). Cochin University of Science and Technology. Retrieved from http://dyuthi.cusat.ac.in/purl/5126

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):

Sudheep Elayidom, M. “Design and Development of data mining Models for the Prediction of Manpower Placement in the Technical Domain.” 2012. Thesis, Cochin University of Science and Technology. Accessed January 17, 2021. http://dyuthi.cusat.ac.in/purl/5126.

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

MLA Handbook (7^th Edition):

Sudheep Elayidom, M. “Design and Development of data mining Models for the Prediction of Manpower Placement in the Technical Domain.” 2012. Web. 17 Jan 2021.

Vancouver:

Sudheep Elayidom M. Design and Development of data mining Models for the Prediction of Manpower Placement in the Technical Domain. [Internet] [Thesis]. Cochin University of Science and Technology; 2012. [cited 2021 Jan 17]. Available from: http://dyuthi.cusat.ac.in/purl/5126.

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

Council of Science Editors:

Sudheep Elayidom M. Design and Development of data mining Models for the Prediction of Manpower Placement in the Technical Domain. [Thesis]. Cochin University of Science and Technology; 2012. Available from: http://dyuthi.cusat.ac.in/purl/5126

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

Indian Institute of Science

21. Sharma, Govind. Sentiment-Driven Topic Analysis Of Song Lyrics.

Degree: MSc Engg, Faculty of Engineering, 2015, Indian Institute of Science

URL: http://etd.iisc.ac.in/handle/2005/2472

► Sentiment Analysis is an area of Computer Science that deals with the impact a document makes on a user. The very field is further sub-divided… (more)

Subjects/Keywords: Song Lyrics; Non-negative Matrix Factorization (NMF); Music Information Retrival; Music Recommendation Engine; Support Vector Machine (SVM); Naive Bayes Classifier (NBC); Sentiment Analysis; Emotion Analysis; Latent Dirichlet Allocation (LDA); Sentiment Clustering; Sentiment Classification; k-Nearest Neighbour Classi er (k-NNC); Computer Science

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APA (6^th Edition):

Sharma, G. (2015). Sentiment-Driven Topic Analysis Of Song Lyrics. (Masters Thesis). Indian Institute of Science. Retrieved from http://etd.iisc.ac.in/handle/2005/2472

Chicago Manual of Style (16^th Edition):

Sharma, Govind. “Sentiment-Driven Topic Analysis Of Song Lyrics.” 2015. Masters Thesis, Indian Institute of Science. Accessed January 17, 2021. http://etd.iisc.ac.in/handle/2005/2472.

MLA Handbook (7^th Edition):

Sharma, Govind. “Sentiment-Driven Topic Analysis Of Song Lyrics.” 2015. Web. 17 Jan 2021.

Vancouver:

Sharma G. Sentiment-Driven Topic Analysis Of Song Lyrics. [Internet] [Masters thesis]. Indian Institute of Science; 2015. [cited 2021 Jan 17]. Available from: http://etd.iisc.ac.in/handle/2005/2472.

Council of Science Editors:

Sharma G. Sentiment-Driven Topic Analysis Of Song Lyrics. [Masters Thesis]. Indian Institute of Science; 2015. Available from: http://etd.iisc.ac.in/handle/2005/2472

Brno University of Technology

22. Guňka, Jiří. Adaptivní klient pro sociální síť Twitter: Adaptive Client for Twitter Social Network.

Degree: 2018, Brno University of Technology

URL: http://hdl.handle.net/11012/54195

► The goal of this term project is create user friendly client of Twitter. They may use methods of machine learning as naive bayes classifier to… (more)

Subjects/Keywords: Twitter; The Jit; Titanium; Appcelator; adaptivní algoritmy; Naivní Bayesův filtr; strojové učení; k-nejbližších sousedů; rozhodovací strom; hyperbolické stromy; stromové mapy; Twitter; The Jit; Titanium; Appcelator; adaptive algorithms; naive bayes classifier; machine learning; k-nearest neighbor; decision tree; hyperbolic tree; treemaps

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APA (6^th Edition):

Guňka, J. (2018). Adaptivní klient pro sociální síť Twitter: Adaptive Client for Twitter Social Network. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/54195

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):

Guňka, Jiří. “Adaptivní klient pro sociální síť Twitter: Adaptive Client for Twitter Social Network.” 2018. Thesis, Brno University of Technology. Accessed January 17, 2021. http://hdl.handle.net/11012/54195.

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

MLA Handbook (7^th Edition):

Guňka, Jiří. “Adaptivní klient pro sociální síť Twitter: Adaptive Client for Twitter Social Network.” 2018. Web. 17 Jan 2021.

Vancouver:

Guňka J. Adaptivní klient pro sociální síť Twitter: Adaptive Client for Twitter Social Network. [Internet] [Thesis]. Brno University of Technology; 2018. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/11012/54195.

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

Council of Science Editors:

Guňka J. Adaptivní klient pro sociální síť Twitter: Adaptive Client for Twitter Social Network. [Thesis]. Brno University of Technology; 2018. Available from: http://hdl.handle.net/11012/54195

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

Brno University of Technology

23. Otrusina, Lubomír. Strojové učení v přirozeném jazyce: Machine-Learning in Natural Language Processing.

Degree: 2020, Brno University of Technology

URL: http://hdl.handle.net/11012/187950

► This beachelor's thesis deals with word sense disambiguation problem using the machine learning techniques. There are shortly presented problems of word sense disambiguation and its… (more)

Subjects/Keywords: strojové učení; učení s učitelem; zpracování přirozeného jazyka; zjednoznačňování slovních významů; naivní Bayesův klasifikátor; Senseval; Semeval; machine learning; supervised learning; natural language processing; word sense disambiguation; naive Bayes classifier; Senseval; Semeval

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

APA (6^th Edition):

Otrusina, L. (2020). Strojové učení v přirozeném jazyce: Machine-Learning in Natural Language Processing. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/187950

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):

Otrusina, Lubomír. “Strojové učení v přirozeném jazyce: Machine-Learning in Natural Language Processing.” 2020. Thesis, Brno University of Technology. Accessed January 17, 2021. http://hdl.handle.net/11012/187950.

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

MLA Handbook (7^th Edition):

Otrusina, Lubomír. “Strojové učení v přirozeném jazyce: Machine-Learning in Natural Language Processing.” 2020. Web. 17 Jan 2021.

Vancouver:

Otrusina L. Strojové učení v přirozeném jazyce: Machine-Learning in Natural Language Processing. [Internet] [Thesis]. Brno University of Technology; 2020. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/11012/187950.

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

Council of Science Editors:

Otrusina L. Strojové učení v přirozeném jazyce: Machine-Learning in Natural Language Processing. [Thesis]. Brno University of Technology; 2020. Available from: http://hdl.handle.net/11012/187950

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

Brno University of Technology

24. Brezánský, Tomáš. Přehled současných přístupů ke klasifikacím: Overview of Actual Approaches to Classifications.

Degree: 2020, Brno University of Technology

URL: http://hdl.handle.net/11012/194991

► This bachelor thesis deals with an overview of current approaches to classifications. It describes various approaches to classifications and their algorithms, focuses on neural networks,… (more)

Subjects/Keywords: klasifikácia; klasifikačné algoritmy; neuronové siete; rozhodovacie stromy; naivný bayesov klasifikátor; algoritmus ID3; Restricted Coulomb Energy (RCE) neurónová sieť; classification; classification algorithms; neural networks; decision trees; naive bayes classifier; ID3 algorithm; Restricted Coulomb Energy (RCE) neural network

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

APA (6^th Edition):

Brezánský, T. (2020). Přehled současných přístupů ke klasifikacím: Overview of Actual Approaches to Classifications. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/194991

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):

Brezánský, Tomáš. “Přehled současných přístupů ke klasifikacím: Overview of Actual Approaches to Classifications.” 2020. Thesis, Brno University of Technology. Accessed January 17, 2021. http://hdl.handle.net/11012/194991.

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

MLA Handbook (7^th Edition):

Brezánský, Tomáš. “Přehled současných přístupů ke klasifikacím: Overview of Actual Approaches to Classifications.” 2020. Web. 17 Jan 2021.

Vancouver:

Brezánský T. Přehled současných přístupů ke klasifikacím: Overview of Actual Approaches to Classifications. [Internet] [Thesis]. Brno University of Technology; 2020. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/11012/194991.

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

Council of Science Editors:

Brezánský T. Přehled současných přístupů ke klasifikacím: Overview of Actual Approaches to Classifications. [Thesis]. Brno University of Technology; 2020. Available from: http://hdl.handle.net/11012/194991

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

Brno University of Technology

25. Zapletal, Ondřej. Srovnání správnosti klasifikace pomocí tradičních modelů a meta-modelů: Comparison of accuracy achieved by traditional models and ensemble methods.

Degree: 2019, Brno University of Technology

URL: http://hdl.handle.net/11012/31719

► This thesis deals with empirical comparison of traditional and meta-learning models in classification tasks. Accuracy of 12 RapidMiner models was statistically compared on 20 data… (more)

Subjects/Keywords: Strojové učení; meta-learning; k-nejbližších sousedů; rozhodovací strom; neuronové sítě; metoda podpůrných vektorů; naivní Bayesův klasifikátor; Bagging; Stacking; Random Forest; Decision Stump; Machine learning; meta-learning; k-nearest neighbor; decision tree; neural net; support vector machines; naive Bayes classifier; Bagging; Stacking; Random Forest; Decision Stump

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

APA (6^th Edition):

Zapletal, O. (2019). Srovnání správnosti klasifikace pomocí tradičních modelů a meta-modelů: Comparison of accuracy achieved by traditional models and ensemble methods. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/31719

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):

Zapletal, Ondřej. “Srovnání správnosti klasifikace pomocí tradičních modelů a meta-modelů: Comparison of accuracy achieved by traditional models and ensemble methods.” 2019. Thesis, Brno University of Technology. Accessed January 17, 2021. http://hdl.handle.net/11012/31719.

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

MLA Handbook (7^th Edition):

Zapletal, Ondřej. “Srovnání správnosti klasifikace pomocí tradičních modelů a meta-modelů: Comparison of accuracy achieved by traditional models and ensemble methods.” 2019. Web. 17 Jan 2021.

Vancouver:

Zapletal O. Srovnání správnosti klasifikace pomocí tradičních modelů a meta-modelů: Comparison of accuracy achieved by traditional models and ensemble methods. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/11012/31719.

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

Council of Science Editors:

Zapletal O. Srovnání správnosti klasifikace pomocí tradičních modelů a meta-modelů: Comparison of accuracy achieved by traditional models and ensemble methods. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/31719

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

Brno University of Technology

26. Vymlátil, Petr. Zjištění Parkinsonovy nemoci na základě analýzy řečového záznamu: Diagnosing Parkinson's disease from analysis of speech recording.

Degree: 2019, Brno University of Technology

URL: http://hdl.handle.net/11012/26564

► This thesis is focused on diagnosing Parkinson’s disease from analysis of speech recording. Introduction of this work deals with description of voice production mechanism, it’s… (more)

Subjects/Keywords: Parkinsonova nemoc; hypokinetická dysartrie; řečový signál; klasifikátory; gaussovy smíšené modely; naivní bayesovský klasifikátor; analýza signálu; formant; předzpracování signálu; jitter; schimmer; mRMR; genetické algoritmy.; Parkinson’s disease; hypokinetic dysarthria; voice signal; classifiers; gaussian mixture models; naive bayes classifier; signal analysis; formant; signal preprocessing; jitter; schimmer; mRMR; genetic algorithms.

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

APA (6^th Edition):

Vymlátil, P. (2019). Zjištění Parkinsonovy nemoci na základě analýzy řečového záznamu: Diagnosing Parkinson's disease from analysis of speech recording. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/26564

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):

Vymlátil, Petr. “Zjištění Parkinsonovy nemoci na základě analýzy řečového záznamu: Diagnosing Parkinson's disease from analysis of speech recording.” 2019. Thesis, Brno University of Technology. Accessed January 17, 2021. http://hdl.handle.net/11012/26564.

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

MLA Handbook (7^th Edition):

Vymlátil, Petr. “Zjištění Parkinsonovy nemoci na základě analýzy řečového záznamu: Diagnosing Parkinson's disease from analysis of speech recording.” 2019. Web. 17 Jan 2021.

Vancouver:

Vymlátil P. Zjištění Parkinsonovy nemoci na základě analýzy řečového záznamu: Diagnosing Parkinson's disease from analysis of speech recording. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/11012/26564.

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

Council of Science Editors:

Vymlátil P. Zjištění Parkinsonovy nemoci na základě analýzy řečového záznamu: Diagnosing Parkinson's disease from analysis of speech recording. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/26564

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

Brno University of Technology

27. Maršánová, Lucie. Analýza experimentálních EKG záznamů: Analysis of experimental ECG.

Degree: 2018, Brno University of Technology

URL: http://hdl.handle.net/11012/38908

► This diploma thesis deals with the analysis of experimental electrograms (EG) recorded from isolated rabbit hearts. The theoretical part is focused on the basic principles… (more)

Subjects/Keywords: Klasifikace experimentálních elektrogramů; ischemie; di-4-ANEPPS; morfologické parametry; metoda nejbližších sousedů; metoda podpůrných vektorů; lineární diskriminační analýza; naivní Bayesův klasifikátor.; Experimental electrogram classification; ischemia; di-4-ANEPPS; morphological parametes; discriminant function analysis; k-Nearest Neighbours; support vector machine; naive Bayes classifier.

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

APA (6^th Edition):

Maršánová, L. (2018). Analýza experimentálních EKG záznamů: Analysis of experimental ECG. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/38908

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):

Maršánová, Lucie. “Analýza experimentálních EKG záznamů: Analysis of experimental ECG.” 2018. Thesis, Brno University of Technology. Accessed January 17, 2021. http://hdl.handle.net/11012/38908.

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

MLA Handbook (7^th Edition):

Maršánová, Lucie. “Analýza experimentálních EKG záznamů: Analysis of experimental ECG.” 2018. Web. 17 Jan 2021.

Vancouver:

Maršánová L. Analýza experimentálních EKG záznamů: Analysis of experimental ECG. [Internet] [Thesis]. Brno University of Technology; 2018. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/11012/38908.

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

Council of Science Editors:

Maršánová L. Analýza experimentálních EKG záznamů: Analysis of experimental ECG. [Thesis]. Brno University of Technology; 2018. Available from: http://hdl.handle.net/11012/38908

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

Brno University of Technology

28. Mackových, Marek. Analýza experimentálních EKG: Analysis of experimental ECG.

Degree: 2018, Brno University of Technology

URL: http://hdl.handle.net/11012/59757

► This thesis is focused on the analysis of experimental ECG records drawn up in isolated rabbit hearts and aims to describe changes in EKG caused… (more)

Subjects/Keywords: EKG; ortogonálne zvody; hypertrofia ľavej komory; ischémia; izolované srdce; morfologické parametre; ROC analýza; AUC; DA; SVM; kNN; naivný bayesov klasifikátor; ECG; orthogonal leads; left ventricular hypertrophy; ischemia; isolated heart; morphological parameters; ROC analysis; AUC; DA; SVM; kNN; Naive Bayes Classifier

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

APA (6^th Edition):

Mackových, M. (2018). Analýza experimentálních EKG: Analysis of experimental ECG. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/59757

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):

Mackových, Marek. “Analýza experimentálních EKG: Analysis of experimental ECG.” 2018. Thesis, Brno University of Technology. Accessed January 17, 2021. http://hdl.handle.net/11012/59757.

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

MLA Handbook (7^th Edition):

Mackových, Marek. “Analýza experimentálních EKG: Analysis of experimental ECG.” 2018. Web. 17 Jan 2021.

Vancouver:

Mackových M. Analýza experimentálních EKG: Analysis of experimental ECG. [Internet] [Thesis]. Brno University of Technology; 2018. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/11012/59757.

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

Council of Science Editors:

Mackových M. Analýza experimentálních EKG: Analysis of experimental ECG. [Thesis]. Brno University of Technology; 2018. Available from: http://hdl.handle.net/11012/59757

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

Laurentian University

29. Nour, Abdala. Markov blanket: efficient strategy for feature subset selection method for high dimensionality microarray cancer datasets .

Degree: 2017, Laurentian University

URL: https://zone.biblio.laurentian.ca/handle/10219/2848

► Currently, feature subset selection methods are very important, especially in areas of application for which datasets with tens or hundreds of thousands of variables (genes)… (more)

▼ Currently, feature subset selection methods are very important, especially in areas of application for which datasets with tens or hundreds of thousands of variables (genes) are available. Feature subset selection methods help us select a small number of variables out of thousands of genes in microarray datasets for a more accurate and balanced classification. Efficient gene selection can be considered as an easy computational hold of the subsequent classification task, and can give subset of gene set without the loss of classification performance. In classifying microarray data, the main objective of gene selection is to search for the genes while keeping the maximum amount of relevant information about the class and minimize classification errors. In this paper, explain the importance of feature subset selection methods in machine learning and data mining fields. Consequently, the analysis of microarray expression was used to check whether global biological differences underlie common pathological features in different types of cancer datasets and identify genes that might anticipate the clinical behavior of this disease. Using the feature subset selection model for gene expression contains large amounts of raw data that needs analyzing to obtain useful information for specific biological and medical applications. One way of finding relevant (and removing redundant ) genes is by using the Bayesian network based on the Markov blanket [1]. We present and compare the performance of the different approaches to feature (genes) subset selection methods based on Wrapper and Markov Blanket models for the five-microarray cancer datasets. The first way depends on the Memetic algorithms (MAs) used for the feature selection method. The second way uses MRMR (Minimum Redundant Maximum Relevant) for feature subset selection hybridized by genetic search optimization techniques and afterwards compares the Markov blanket model’s performance with the most common classical classification algorithms for the selected set of features. For the memetic algorithm, we present a comparison between two embedded approaches for feature subset selection which are the wrapper filter for feature selection algorithm (WFFSA) and Markov Blanket Embedded Genetic Algorithm (MBEGA). The memetic algorithm depends on genetic operators (crossover, mutation) and the dedicated local search procedure. For comparisons, we depend on two evaluations techniques for learning and testing data which are 10-Kfold cross validation and 30-Bootstraping. The results of the memetic algorithm clearly show MBEGA often outperforms WFFSA methods by yielding more significant differentiation among different microarray cancer datasets. In the second part of this paper, we focus mainly on MRMR for feature subset selection methods and the Bayesian network based on Markov blanket (MB) model that are useful for building a good predictor and defying the curse of dimensionality to improve prediction performance. These methods cover a wide range of…

Subjects/Keywords: Microarray datasets; feature selection methods; genetic algorithms; memetic algorithms; overfitting problem; fitness function; crossover; mutation; Markov Blanket; minimum redundancy-maximum relevant,; support vector machine; naive Bayes; k-nearest-neighbor; ensemble classifier; Bayesian networks

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

APA (6^th Edition):

Nour, A. (2017). Markov blanket: efficient strategy for feature subset selection method for high dimensionality microarray cancer datasets . (Thesis). Laurentian University. Retrieved from https://zone.biblio.laurentian.ca/handle/10219/2848

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):

Nour, Abdala. “Markov blanket: efficient strategy for feature subset selection method for high dimensionality microarray cancer datasets .” 2017. Thesis, Laurentian University. Accessed January 17, 2021. https://zone.biblio.laurentian.ca/handle/10219/2848.

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

MLA Handbook (7^th Edition):

Nour, Abdala. “Markov blanket: efficient strategy for feature subset selection method for high dimensionality microarray cancer datasets .” 2017. Web. 17 Jan 2021.

Vancouver:

Nour A. Markov blanket: efficient strategy for feature subset selection method for high dimensionality microarray cancer datasets . [Internet] [Thesis]. Laurentian University; 2017. [cited 2021 Jan 17]. Available from: https://zone.biblio.laurentian.ca/handle/10219/2848.

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

Council of Science Editors:

Nour A. Markov blanket: efficient strategy for feature subset selection method for high dimensionality microarray cancer datasets . [Thesis]. Laurentian University; 2017. Available from: https://zone.biblio.laurentian.ca/handle/10219/2848

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

Kansas State University

30. Anderson, Michael P. Bayesian classification of DNA barcodes.

Degree: PhD, Department of Statistics, 2009, Kansas State University

URL: http://hdl.handle.net/2097/2247

► DNA barcodes are short strands of nucleotide bases taken from the cytochrome c oxidase subunit 1 (COI) of the mitochondrial DNA (mtDNA). A single barcode… (more)

Subjects/Keywords: DNA Barcodes; Bayesian Classification; Species Discovery; Naive Bayes Classifier; Sequential Analysis; High-dimensional Data; Statistics (0463)

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

APA (6^th Edition):

Anderson, M. P. (2009). Bayesian classification of DNA barcodes. (Doctoral Dissertation). Kansas State University. Retrieved from http://hdl.handle.net/2097/2247

Chicago Manual of Style (16^th Edition):

Anderson, Michael P. “Bayesian classification of DNA barcodes.” 2009. Doctoral Dissertation, Kansas State University. Accessed January 17, 2021. http://hdl.handle.net/2097/2247.

MLA Handbook (7^th Edition):

Anderson, Michael P. “Bayesian classification of DNA barcodes.” 2009. Web. 17 Jan 2021.

Vancouver:

Anderson MP. Bayesian classification of DNA barcodes. [Internet] [Doctoral dissertation]. Kansas State University; 2009. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/2097/2247.

Council of Science Editors:

Anderson MP. Bayesian classification of DNA barcodes. [Doctoral Dissertation]. Kansas State University; 2009. Available from: http://hdl.handle.net/2097/2247

Open Access Theses and Dissertations