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You searched for subject:(Feature selection). Showing records 1 – 30 of 575 total matches.

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University of Saskatchewan

1. Dong, Mei. Feature Selection Bias in Assessing the Predictivity of SNPs for Alzheimer's Disease.

Degree: 2019, University of Saskatchewan

 In the context of identifying related SNPs for a phenotype of interest (e.g., a disease status), we consider the problem of assessing the predictivity of… (more)

Subjects/Keywords: Feature Selection bias; Cross-validation; Predictive Analysis; GWAS; Alzheimer's Disease

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

APA (6th Edition):

Dong, M. (2019). Feature Selection Bias in Assessing the Predictivity of SNPs for Alzheimer's Disease. (Thesis). University of Saskatchewan. Retrieved from http://hdl.handle.net/10388/12118

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

Chicago Manual of Style (16th Edition):

Dong, Mei. “Feature Selection Bias in Assessing the Predictivity of SNPs for Alzheimer's Disease.” 2019. Thesis, University of Saskatchewan. Accessed June 19, 2019. http://hdl.handle.net/10388/12118.

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

MLA Handbook (7th Edition):

Dong, Mei. “Feature Selection Bias in Assessing the Predictivity of SNPs for Alzheimer's Disease.” 2019. Web. 19 Jun 2019.

Vancouver:

Dong M. Feature Selection Bias in Assessing the Predictivity of SNPs for Alzheimer's Disease. [Internet] [Thesis]. University of Saskatchewan; 2019. [cited 2019 Jun 19]. Available from: http://hdl.handle.net/10388/12118.

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

Council of Science Editors:

Dong M. Feature Selection Bias in Assessing the Predictivity of SNPs for Alzheimer's Disease. [Thesis]. University of Saskatchewan; 2019. Available from: http://hdl.handle.net/10388/12118

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


San Jose State University

2. Badshah, Mustafa. Sensor - Based Human Activity Recognition Using Smartphones.

Degree: MS, Computer Science, 2019, San Jose State University

  It is a significant technical and computational task to provide precise information regarding the activity performed by a human and find patterns of their… (more)

Subjects/Keywords: Human activity recognition; machine learning; mobile sensors; accelerometer; gyroscope; feature selection; RNN; Artificial Intelligence and Robotics

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APA (6th Edition):

Badshah, M. (2019). Sensor - Based Human Activity Recognition Using Smartphones. (Masters Thesis). San Jose State University. Retrieved from https://scholarworks.sjsu.edu/etd_projects/677

Chicago Manual of Style (16th Edition):

Badshah, Mustafa. “Sensor - Based Human Activity Recognition Using Smartphones.” 2019. Masters Thesis, San Jose State University. Accessed June 19, 2019. https://scholarworks.sjsu.edu/etd_projects/677.

MLA Handbook (7th Edition):

Badshah, Mustafa. “Sensor - Based Human Activity Recognition Using Smartphones.” 2019. Web. 19 Jun 2019.

Vancouver:

Badshah M. Sensor - Based Human Activity Recognition Using Smartphones. [Internet] [Masters thesis]. San Jose State University; 2019. [cited 2019 Jun 19]. Available from: https://scholarworks.sjsu.edu/etd_projects/677.

Council of Science Editors:

Badshah M. Sensor - Based Human Activity Recognition Using Smartphones. [Masters Thesis]. San Jose State University; 2019. Available from: https://scholarworks.sjsu.edu/etd_projects/677


Delft University of Technology

3. Rotteveel, E. Influence of inland vessel stern shape aspects on propulsive performance: Derivation of insights and guidelines based on a computational study.

Degree: 2019, Delft University of Technology

 This research focuses on identifying the most important stern shape aspects, with regard to resistance and propulsion power, of inland ships. Such information should help… (more)

Subjects/Keywords: inland navigation; Shallow water; ship design; Computational fluid dynamics (CFD); optimisation; Response surface methodology; Feature selection; propulsion; ship hydrodynamics

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APA (6th Edition):

Rotteveel, E. (2019). Influence of inland vessel stern shape aspects on propulsive performance: Derivation of insights and guidelines based on a computational study. (Doctoral Dissertation). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:8d8c14e3-cdfb-4e15-8314-35dc296fdbde ; urn:NBN:nl:ui:24-uuid:8d8c14e3-cdfb-4e15-8314-35dc296fdbde ; 8d8c14e3-cdfb-4e15-8314-35dc296fdbde ; urn:isbn:978-94-6380-242-0 ; 10.4233/uuid:8d8c14e3-cdfb-4e15-8314-35dc296fdbde ; urn:NBN:nl:ui:24-uuid:8d8c14e3-cdfb-4e15-8314-35dc296fdbde ; http://resolver.tudelft.nl/uuid:8d8c14e3-cdfb-4e15-8314-35dc296fdbde

Chicago Manual of Style (16th Edition):

Rotteveel, E. “Influence of inland vessel stern shape aspects on propulsive performance: Derivation of insights and guidelines based on a computational study.” 2019. Doctoral Dissertation, Delft University of Technology. Accessed June 19, 2019. http://resolver.tudelft.nl/uuid:8d8c14e3-cdfb-4e15-8314-35dc296fdbde ; urn:NBN:nl:ui:24-uuid:8d8c14e3-cdfb-4e15-8314-35dc296fdbde ; 8d8c14e3-cdfb-4e15-8314-35dc296fdbde ; urn:isbn:978-94-6380-242-0 ; 10.4233/uuid:8d8c14e3-cdfb-4e15-8314-35dc296fdbde ; urn:NBN:nl:ui:24-uuid:8d8c14e3-cdfb-4e15-8314-35dc296fdbde ; http://resolver.tudelft.nl/uuid:8d8c14e3-cdfb-4e15-8314-35dc296fdbde.

MLA Handbook (7th Edition):

Rotteveel, E. “Influence of inland vessel stern shape aspects on propulsive performance: Derivation of insights and guidelines based on a computational study.” 2019. Web. 19 Jun 2019.

Vancouver:

Rotteveel E. Influence of inland vessel stern shape aspects on propulsive performance: Derivation of insights and guidelines based on a computational study. [Internet] [Doctoral dissertation]. Delft University of Technology; 2019. [cited 2019 Jun 19]. Available from: http://resolver.tudelft.nl/uuid:8d8c14e3-cdfb-4e15-8314-35dc296fdbde ; urn:NBN:nl:ui:24-uuid:8d8c14e3-cdfb-4e15-8314-35dc296fdbde ; 8d8c14e3-cdfb-4e15-8314-35dc296fdbde ; urn:isbn:978-94-6380-242-0 ; 10.4233/uuid:8d8c14e3-cdfb-4e15-8314-35dc296fdbde ; urn:NBN:nl:ui:24-uuid:8d8c14e3-cdfb-4e15-8314-35dc296fdbde ; http://resolver.tudelft.nl/uuid:8d8c14e3-cdfb-4e15-8314-35dc296fdbde.

Council of Science Editors:

Rotteveel E. Influence of inland vessel stern shape aspects on propulsive performance: Derivation of insights and guidelines based on a computational study. [Doctoral Dissertation]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:8d8c14e3-cdfb-4e15-8314-35dc296fdbde ; urn:NBN:nl:ui:24-uuid:8d8c14e3-cdfb-4e15-8314-35dc296fdbde ; 8d8c14e3-cdfb-4e15-8314-35dc296fdbde ; urn:isbn:978-94-6380-242-0 ; 10.4233/uuid:8d8c14e3-cdfb-4e15-8314-35dc296fdbde ; urn:NBN:nl:ui:24-uuid:8d8c14e3-cdfb-4e15-8314-35dc296fdbde ; http://resolver.tudelft.nl/uuid:8d8c14e3-cdfb-4e15-8314-35dc296fdbde

4. Mlakar, Uroš. Razpoznavanje čustvenih izrazov osebe iz slikovnega materiala z algoritmom diferencialne evolucije za izbiro značilnic.

Degree: 2019, Univerza v Mariboru

V disertaciji se ukvarjamo z razvojem učinkovitega programskega sistema za izbiro značilnic, na primeru aplikacije prepoznavanja čustvenih izrazov. Predlagan sistem, ki prepoznava sedem prototipnih čustvenih… (more)

Subjects/Keywords: razpoznavanje čustvenih izrazov,izbira značilnic,diferencialna evolucija,razlike vektorjev značilnic,večkriterijska optimizacija; facial expression recognition,feature selection,differential evolution,feature vector differences,multi-objective optimization; info:eu-repo/classification/udc/004.932(043.3)

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APA (6th Edition):

Mlakar, U. (2019). Razpoznavanje čustvenih izrazov osebe iz slikovnega materiala z algoritmom diferencialne evolucije za izbiro značilnic. (Doctoral Dissertation). Univerza v Mariboru. Retrieved from https://dk.um.si/IzpisGradiva.php?id=72669 ; https://dk.um.si/Dokument.php?id=133022&dn= ; https://plus.si.cobiss.net/opac7/bib/22195478?lang=sl

Chicago Manual of Style (16th Edition):

Mlakar, Uroš. “Razpoznavanje čustvenih izrazov osebe iz slikovnega materiala z algoritmom diferencialne evolucije za izbiro značilnic.” 2019. Doctoral Dissertation, Univerza v Mariboru. Accessed June 19, 2019. https://dk.um.si/IzpisGradiva.php?id=72669 ; https://dk.um.si/Dokument.php?id=133022&dn= ; https://plus.si.cobiss.net/opac7/bib/22195478?lang=sl.

MLA Handbook (7th Edition):

Mlakar, Uroš. “Razpoznavanje čustvenih izrazov osebe iz slikovnega materiala z algoritmom diferencialne evolucije za izbiro značilnic.” 2019. Web. 19 Jun 2019.

Vancouver:

Mlakar U. Razpoznavanje čustvenih izrazov osebe iz slikovnega materiala z algoritmom diferencialne evolucije za izbiro značilnic. [Internet] [Doctoral dissertation]. Univerza v Mariboru; 2019. [cited 2019 Jun 19]. Available from: https://dk.um.si/IzpisGradiva.php?id=72669 ; https://dk.um.si/Dokument.php?id=133022&dn= ; https://plus.si.cobiss.net/opac7/bib/22195478?lang=sl.

Council of Science Editors:

Mlakar U. Razpoznavanje čustvenih izrazov osebe iz slikovnega materiala z algoritmom diferencialne evolucije za izbiro značilnic. [Doctoral Dissertation]. Univerza v Mariboru; 2019. Available from: https://dk.um.si/IzpisGradiva.php?id=72669 ; https://dk.um.si/Dokument.php?id=133022&dn= ; https://plus.si.cobiss.net/opac7/bib/22195478?lang=sl


University of Washington

5. LI, QIAOZHI. Investigation of Extending Feature Selection Algorithms to Explicit Feature Selection in Kernel Space.

Degree: 2019, University of Washington

Feature selection methods play important roles in the area of machine learning. Being a part of prepossessing, the technology of feature selection can select useful… (more)

Subjects/Keywords: feature selection; high-dimensional; kernel trick; machine learning; nonlinear data; Computer science; Computer science and systems

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APA (6th Edition):

LI, Q. (2019). Investigation of Extending Feature Selection Algorithms to Explicit Feature Selection in Kernel Space. (Thesis). University of Washington. Retrieved from http://hdl.handle.net/1773/43272

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

Chicago Manual of Style (16th Edition):

LI, QIAOZHI. “Investigation of Extending Feature Selection Algorithms to Explicit Feature Selection in Kernel Space.” 2019. Thesis, University of Washington. Accessed June 19, 2019. http://hdl.handle.net/1773/43272.

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

MLA Handbook (7th Edition):

LI, QIAOZHI. “Investigation of Extending Feature Selection Algorithms to Explicit Feature Selection in Kernel Space.” 2019. Web. 19 Jun 2019.

Vancouver:

LI Q. Investigation of Extending Feature Selection Algorithms to Explicit Feature Selection in Kernel Space. [Internet] [Thesis]. University of Washington; 2019. [cited 2019 Jun 19]. Available from: http://hdl.handle.net/1773/43272.

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

Council of Science Editors:

LI Q. Investigation of Extending Feature Selection Algorithms to Explicit Feature Selection in Kernel Space. [Thesis]. University of Washington; 2019. Available from: http://hdl.handle.net/1773/43272

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

6. Apolónia, João. Seleção de atributos de dados inconsistentes .

Degree: 2019, Universidade Aberta

 O tratamento de conjuntos de dados de grande dimensão é uma questão que é recorrente nos dias de hoje e cuja tarefa não é simples,… (more)

Subjects/Keywords: Data mining; Seleção de atributos; Inconsistência de dados; Análise Lógica de Dados (LAD); Análise Lógica de Dados Inconsistentes (LAID); Feature selection; LAID; Data inconsistency; HDF5; Python; INCD

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APA (6th Edition):

Apolónia, J. (2019). Seleção de atributos de dados inconsistentes . (Masters Thesis). Universidade Aberta. Retrieved from http://hdl.handle.net/10400.2/8066

Chicago Manual of Style (16th Edition):

Apolónia, João. “Seleção de atributos de dados inconsistentes .” 2019. Masters Thesis, Universidade Aberta. Accessed June 19, 2019. http://hdl.handle.net/10400.2/8066.

MLA Handbook (7th Edition):

Apolónia, João. “Seleção de atributos de dados inconsistentes .” 2019. Web. 19 Jun 2019.

Vancouver:

Apolónia J. Seleção de atributos de dados inconsistentes . [Internet] [Masters thesis]. Universidade Aberta; 2019. [cited 2019 Jun 19]. Available from: http://hdl.handle.net/10400.2/8066.

Council of Science Editors:

Apolónia J. Seleção de atributos de dados inconsistentes . [Masters Thesis]. Universidade Aberta; 2019. Available from: http://hdl.handle.net/10400.2/8066


Virginia Commonwealth University

7. Gonzalez Lopez, Jorge. Distributed multi-label learning on Apache Spark.

Degree: PhD, Computer Science, 2019, Virginia Commonwealth University

 This thesis proposes a series of multi-label learning algorithms for classification and feature selection implemented on the Apache Spark distributed computing model. Five approaches for… (more)

Subjects/Keywords: multi-label; apache spark; feature selection; mutual information; Artificial Intelligence and Robotics; Numerical Analysis and Scientific Computing; Theory and Algorithms

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APA (6th Edition):

Gonzalez Lopez, J. (2019). Distributed multi-label learning on Apache Spark. (Doctoral Dissertation). Virginia Commonwealth University. Retrieved from https://scholarscompass.vcu.edu/etd/5775

Chicago Manual of Style (16th Edition):

Gonzalez Lopez, Jorge. “Distributed multi-label learning on Apache Spark.” 2019. Doctoral Dissertation, Virginia Commonwealth University. Accessed June 19, 2019. https://scholarscompass.vcu.edu/etd/5775.

MLA Handbook (7th Edition):

Gonzalez Lopez, Jorge. “Distributed multi-label learning on Apache Spark.” 2019. Web. 19 Jun 2019.

Vancouver:

Gonzalez Lopez J. Distributed multi-label learning on Apache Spark. [Internet] [Doctoral dissertation]. Virginia Commonwealth University; 2019. [cited 2019 Jun 19]. Available from: https://scholarscompass.vcu.edu/etd/5775.

Council of Science Editors:

Gonzalez Lopez J. Distributed multi-label learning on Apache Spark. [Doctoral Dissertation]. Virginia Commonwealth University; 2019. Available from: https://scholarscompass.vcu.edu/etd/5775


University of Newcastle

8. Jimenez, Francia. The multi-objective approach to solve the (alpha, beta)-k feature set problem using memetic algorithms.

Degree: PhD, 2019, University of Newcastle

Research Doctorate - Doctor of Philosophy (PhD)

In many application areas, the decision-making process is enhanced by the information obtained from analyzing data. In fact,… (more)

Subjects/Keywords: Feature Selection (FS); k-Feature Set Problem (k-FS); α; β)-k-Feature Set Problem (ABkFS); data integration

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APA (6th Edition):

Jimenez, F. (2019). The multi-objective approach to solve the (alpha, beta)-k feature set problem using memetic algorithms. (Doctoral Dissertation). University of Newcastle. Retrieved from http://hdl.handle.net/1959.13/1400428

Chicago Manual of Style (16th Edition):

Jimenez, Francia. “The multi-objective approach to solve the (alpha, beta)-k feature set problem using memetic algorithms.” 2019. Doctoral Dissertation, University of Newcastle. Accessed June 19, 2019. http://hdl.handle.net/1959.13/1400428.

MLA Handbook (7th Edition):

Jimenez, Francia. “The multi-objective approach to solve the (alpha, beta)-k feature set problem using memetic algorithms.” 2019. Web. 19 Jun 2019.

Vancouver:

Jimenez F. The multi-objective approach to solve the (alpha, beta)-k feature set problem using memetic algorithms. [Internet] [Doctoral dissertation]. University of Newcastle; 2019. [cited 2019 Jun 19]. Available from: http://hdl.handle.net/1959.13/1400428.

Council of Science Editors:

Jimenez F. The multi-objective approach to solve the (alpha, beta)-k feature set problem using memetic algorithms. [Doctoral Dissertation]. University of Newcastle; 2019. Available from: http://hdl.handle.net/1959.13/1400428


University of Newcastle

9. Salehipour, Amir. Combinatorial optimization methods for the (alpha,beta)-k Feature Set Problem.

Degree: PhD, 2019, University of Newcastle

Research Doctorate - Doctor of Philosophy (PhD)

This PhD research thesis proposes novel and efficient combinatorial optimization-based solution methods for the (alpha,beta)-k Feature Set Problem.… (more)

Subjects/Keywords: feature selection; combinatorial optimization; integer programming; heuristics; matheuristics

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APA (6th Edition):

Salehipour, A. (2019). Combinatorial optimization methods for the (alpha,beta)-k Feature Set Problem. (Doctoral Dissertation). University of Newcastle. Retrieved from http://hdl.handle.net/1959.13/1400399

Chicago Manual of Style (16th Edition):

Salehipour, Amir. “Combinatorial optimization methods for the (alpha,beta)-k Feature Set Problem.” 2019. Doctoral Dissertation, University of Newcastle. Accessed June 19, 2019. http://hdl.handle.net/1959.13/1400399.

MLA Handbook (7th Edition):

Salehipour, Amir. “Combinatorial optimization methods for the (alpha,beta)-k Feature Set Problem.” 2019. Web. 19 Jun 2019.

Vancouver:

Salehipour A. Combinatorial optimization methods for the (alpha,beta)-k Feature Set Problem. [Internet] [Doctoral dissertation]. University of Newcastle; 2019. [cited 2019 Jun 19]. Available from: http://hdl.handle.net/1959.13/1400399.

Council of Science Editors:

Salehipour A. Combinatorial optimization methods for the (alpha,beta)-k Feature Set Problem. [Doctoral Dissertation]. University of Newcastle; 2019. Available from: http://hdl.handle.net/1959.13/1400399


RMIT University

10. Song, H. Evolutionary multivariate time series prediction.

Degree: 2019, RMIT University

 Multivariate time series (MTS) prediction plays a significant role in many practical data mining applications, such as finance, energy supply, and medical care domains. Over… (more)

Subjects/Keywords: Fields of Research; Multivariate time series prediction; Evolutionary algorithm; Ensemble learning; Feature extraction; Feature selection; Single-objective optimization; Multi-objective optimization

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APA (6th Edition):

Song, H. (2019). Evolutionary multivariate time series prediction. (Thesis). RMIT University. Retrieved from http://researchbank.rmit.edu.au/view/rmit:162681

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

Chicago Manual of Style (16th Edition):

Song, H. “Evolutionary multivariate time series prediction.” 2019. Thesis, RMIT University. Accessed June 19, 2019. http://researchbank.rmit.edu.au/view/rmit:162681.

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

MLA Handbook (7th Edition):

Song, H. “Evolutionary multivariate time series prediction.” 2019. Web. 19 Jun 2019.

Vancouver:

Song H. Evolutionary multivariate time series prediction. [Internet] [Thesis]. RMIT University; 2019. [cited 2019 Jun 19]. Available from: http://researchbank.rmit.edu.au/view/rmit:162681.

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

Council of Science Editors:

Song H. Evolutionary multivariate time series prediction. [Thesis]. RMIT University; 2019. Available from: http://researchbank.rmit.edu.au/view/rmit:162681

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


University of New South Wales

11. Mirtalaie, Monireh Alsadat. Feature drift-based framework for novel idea recommendation in new product development.

Degree: Business, 2019, University of New South Wales

 In these competitive times, designers need to constantly update their tangible products with new features and functionalities to retain market share. This is especially important… (more)

Subjects/Keywords: Idea generation; New product development; Sentiment analysis; Idea selection; Fuzzy decision making; Feature drift

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APA (6th Edition):

Mirtalaie, M. A. (2019). Feature drift-based framework for novel idea recommendation in new product development. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/62233 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:58348/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Mirtalaie, Monireh Alsadat. “Feature drift-based framework for novel idea recommendation in new product development.” 2019. Doctoral Dissertation, University of New South Wales. Accessed June 19, 2019. http://handle.unsw.edu.au/1959.4/62233 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:58348/SOURCE02?view=true.

MLA Handbook (7th Edition):

Mirtalaie, Monireh Alsadat. “Feature drift-based framework for novel idea recommendation in new product development.” 2019. Web. 19 Jun 2019.

Vancouver:

Mirtalaie MA. Feature drift-based framework for novel idea recommendation in new product development. [Internet] [Doctoral dissertation]. University of New South Wales; 2019. [cited 2019 Jun 19]. Available from: http://handle.unsw.edu.au/1959.4/62233 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:58348/SOURCE02?view=true.

Council of Science Editors:

Mirtalaie MA. Feature drift-based framework for novel idea recommendation in new product development. [Doctoral Dissertation]. University of New South Wales; 2019. Available from: http://handle.unsw.edu.au/1959.4/62233 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:58348/SOURCE02?view=true

12. Zistler, Marina. Advancement of Data-Driven Short-Term Flood Predictions on an Urbanized Watershed Using Preprocessing Techniques.

Degree: MA -MA, Information Systems and Technology, 2018, York University

 Supervised classification can be applied for short-term predictions of hydrological events in cases where the label of the event rather than its magnitude is crucial,… (more)

Subjects/Keywords: Information technology; Machine learning; Flood prediction; Time-series; Time-delay embedding; Classification; Imbalanced data; Feature selection; Flash floods; Rainfall-runoff; Phase space

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APA (6th Edition):

Zistler, M. (2018). Advancement of Data-Driven Short-Term Flood Predictions on an Urbanized Watershed Using Preprocessing Techniques. (Masters Thesis). York University. Retrieved from http://hdl.handle.net/10315/35532

Chicago Manual of Style (16th Edition):

Zistler, Marina. “Advancement of Data-Driven Short-Term Flood Predictions on an Urbanized Watershed Using Preprocessing Techniques.” 2018. Masters Thesis, York University. Accessed June 19, 2019. http://hdl.handle.net/10315/35532.

MLA Handbook (7th Edition):

Zistler, Marina. “Advancement of Data-Driven Short-Term Flood Predictions on an Urbanized Watershed Using Preprocessing Techniques.” 2018. Web. 19 Jun 2019.

Vancouver:

Zistler M. Advancement of Data-Driven Short-Term Flood Predictions on an Urbanized Watershed Using Preprocessing Techniques. [Internet] [Masters thesis]. York University; 2018. [cited 2019 Jun 19]. Available from: http://hdl.handle.net/10315/35532.

Council of Science Editors:

Zistler M. Advancement of Data-Driven Short-Term Flood Predictions on an Urbanized Watershed Using Preprocessing Techniques. [Masters Thesis]. York University; 2018. Available from: http://hdl.handle.net/10315/35532


Victoria University of Wellington

13. Nguyen, Bach Hoai. Evolutionary Computation for Feature Selection in Classification.

Degree: 2018, Victoria University of Wellington

 Classification aims to identify a class label of an instance according to the information from its characteristics or features. Unfortunately, many classification problems have a… (more)

Subjects/Keywords: Feature Selection; Evolutionary Computation; Classification

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APA (6th Edition):

Nguyen, B. H. (2018). Evolutionary Computation for Feature Selection in Classification. (Doctoral Dissertation). Victoria University of Wellington. Retrieved from http://hdl.handle.net/10063/7821

Chicago Manual of Style (16th Edition):

Nguyen, Bach Hoai. “Evolutionary Computation for Feature Selection in Classification.” 2018. Doctoral Dissertation, Victoria University of Wellington. Accessed June 19, 2019. http://hdl.handle.net/10063/7821.

MLA Handbook (7th Edition):

Nguyen, Bach Hoai. “Evolutionary Computation for Feature Selection in Classification.” 2018. Web. 19 Jun 2019.

Vancouver:

Nguyen BH. Evolutionary Computation for Feature Selection in Classification. [Internet] [Doctoral dissertation]. Victoria University of Wellington; 2018. [cited 2019 Jun 19]. Available from: http://hdl.handle.net/10063/7821.

Council of Science Editors:

Nguyen BH. Evolutionary Computation for Feature Selection in Classification. [Doctoral Dissertation]. Victoria University of Wellington; 2018. Available from: http://hdl.handle.net/10063/7821


Texas A&M University

14. Tracy, James L. Random Subset Feature Selection for Ecological Niche Modeling of Wildfire Activity and the Monarch Butterfly.

Degree: PhD, Entomology, 2018, Texas A&M University

 Correlative ecological niche models (ENMs) are essential for investigating distributions of species and natural phenomena via environmental correlates across broad fields, including entomology and pyrogeography… (more)

Subjects/Keywords: Random Feature Selection; Feature Subset Ensemble; Species Distribution Model; Pyrogeography; Danaus plexippus; Migratory Niche Model; Kernel Density Estimation Migratory Model; Insect Roadkill Niche Model

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

APA (6th Edition):

Tracy, J. L. (2018). Random Subset Feature Selection for Ecological Niche Modeling of Wildfire Activity and the Monarch Butterfly. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/174342

Chicago Manual of Style (16th Edition):

Tracy, James L. “Random Subset Feature Selection for Ecological Niche Modeling of Wildfire Activity and the Monarch Butterfly.” 2018. Doctoral Dissertation, Texas A&M University. Accessed June 19, 2019. http://hdl.handle.net/1969.1/174342.

MLA Handbook (7th Edition):

Tracy, James L. “Random Subset Feature Selection for Ecological Niche Modeling of Wildfire Activity and the Monarch Butterfly.” 2018. Web. 19 Jun 2019.

Vancouver:

Tracy JL. Random Subset Feature Selection for Ecological Niche Modeling of Wildfire Activity and the Monarch Butterfly. [Internet] [Doctoral dissertation]. Texas A&M University; 2018. [cited 2019 Jun 19]. Available from: http://hdl.handle.net/1969.1/174342.

Council of Science Editors:

Tracy JL. Random Subset Feature Selection for Ecological Niche Modeling of Wildfire Activity and the Monarch Butterfly. [Doctoral Dissertation]. Texas A&M University; 2018. Available from: http://hdl.handle.net/1969.1/174342

15. Rommel, Cédric. Exploration de données pour l'optimisation de trajectoires aériennes : Data analysis for aircraft trajectory optimization.

Degree: Docteur es, Mathématiques appliquées, 2018, Paris Saclay

Cette thèse porte sur l'utilisation de données de vols pour l'optimisation de trajectoires de montée vis-à-vis de la consommation de carburant.Dans un premier temps nous… (more)

Subjects/Keywords: Optimisation de trajectoires; Identification de systèmes dynamiques; Selection de variables; Apprentissage multi-Tâches; Estimation de densité; Analyse de données fonctionnelles; Trajectory optimization; System identification; Structured feature selection; Multi-Task learning; Density estimation; Functional data analysis; 519

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

APA (6th Edition):

Rommel, C. (2018). Exploration de données pour l'optimisation de trajectoires aériennes : Data analysis for aircraft trajectory optimization. (Doctoral Dissertation). Paris Saclay. Retrieved from http://www.theses.fr/2018SACLX066

Chicago Manual of Style (16th Edition):

Rommel, Cédric. “Exploration de données pour l'optimisation de trajectoires aériennes : Data analysis for aircraft trajectory optimization.” 2018. Doctoral Dissertation, Paris Saclay. Accessed June 19, 2019. http://www.theses.fr/2018SACLX066.

MLA Handbook (7th Edition):

Rommel, Cédric. “Exploration de données pour l'optimisation de trajectoires aériennes : Data analysis for aircraft trajectory optimization.” 2018. Web. 19 Jun 2019.

Vancouver:

Rommel C. Exploration de données pour l'optimisation de trajectoires aériennes : Data analysis for aircraft trajectory optimization. [Internet] [Doctoral dissertation]. Paris Saclay; 2018. [cited 2019 Jun 19]. Available from: http://www.theses.fr/2018SACLX066.

Council of Science Editors:

Rommel C. Exploration de données pour l'optimisation de trajectoires aériennes : Data analysis for aircraft trajectory optimization. [Doctoral Dissertation]. Paris Saclay; 2018. Available from: http://www.theses.fr/2018SACLX066


Victoria University of Wellington

16. Tran, Cao Truong. Evolutionary Machine Learning for Classification with Incomplete Data.

Degree: 2018, Victoria University of Wellington

 Classification is a major task in machine learning and data mining. Many real-world datasets suffer from the unavoidable issue of missing values. Classification with incomplete… (more)

Subjects/Keywords: Incomplete data; Missing data; Classification; Machine learning; Evolutionary computation; Genetic programming; Ensemble learning; Feature selection; Feature construction

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

APA (6th Edition):

Tran, C. T. (2018). Evolutionary Machine Learning for Classification with Incomplete Data. (Doctoral Dissertation). Victoria University of Wellington. Retrieved from http://hdl.handle.net/10063/7639

Chicago Manual of Style (16th Edition):

Tran, Cao Truong. “Evolutionary Machine Learning for Classification with Incomplete Data.” 2018. Doctoral Dissertation, Victoria University of Wellington. Accessed June 19, 2019. http://hdl.handle.net/10063/7639.

MLA Handbook (7th Edition):

Tran, Cao Truong. “Evolutionary Machine Learning for Classification with Incomplete Data.” 2018. Web. 19 Jun 2019.

Vancouver:

Tran CT. Evolutionary Machine Learning for Classification with Incomplete Data. [Internet] [Doctoral dissertation]. Victoria University of Wellington; 2018. [cited 2019 Jun 19]. Available from: http://hdl.handle.net/10063/7639.

Council of Science Editors:

Tran CT. Evolutionary Machine Learning for Classification with Incomplete Data. [Doctoral Dissertation]. Victoria University of Wellington; 2018. Available from: http://hdl.handle.net/10063/7639


University of Waterloo

17. Sequiera, Royal. Simple Convolutional Neural Networks with Linguistically-Annotated Input for Answer Selection in Question Answering.

Degree: 2018, University of Waterloo

 With the advent of deep learning methods, researchers have been increasingly preferring deep learning methods over decades-old feature-engineering-inspired work in Natural Language Processing (NLP). The… (more)

Subjects/Keywords: Natural Language Processing; NLP; Question Answering; Answer selection; CNN; Feature engineering; neural networks

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APA (6th Edition):

Sequiera, R. (2018). Simple Convolutional Neural Networks with Linguistically-Annotated Input for Answer Selection in Question Answering. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/13570

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

Chicago Manual of Style (16th Edition):

Sequiera, Royal. “Simple Convolutional Neural Networks with Linguistically-Annotated Input for Answer Selection in Question Answering.” 2018. Thesis, University of Waterloo. Accessed June 19, 2019. http://hdl.handle.net/10012/13570.

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

MLA Handbook (7th Edition):

Sequiera, Royal. “Simple Convolutional Neural Networks with Linguistically-Annotated Input for Answer Selection in Question Answering.” 2018. Web. 19 Jun 2019.

Vancouver:

Sequiera R. Simple Convolutional Neural Networks with Linguistically-Annotated Input for Answer Selection in Question Answering. [Internet] [Thesis]. University of Waterloo; 2018. [cited 2019 Jun 19]. Available from: http://hdl.handle.net/10012/13570.

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

Council of Science Editors:

Sequiera R. Simple Convolutional Neural Networks with Linguistically-Annotated Input for Answer Selection in Question Answering. [Thesis]. University of Waterloo; 2018. Available from: http://hdl.handle.net/10012/13570

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


NSYSU

18. Lin, Ji-Wei. Selection of the most informative schemes for multi-locus sequence typing.

Degree: Master, Institute Of Medical Science And Technology, 2018, NSYSU

 To investigate and surveillance the foodborne disease outbreak caused by bacteria, molecular sequence subtyping method would be employed. In our study, we build an open-access… (more)

Subjects/Keywords: Feature selection; Molecular subtyping; Typing scheme selection; Foodborne disease; Whole-genome multilocus sequence typing (wgMLST); Next generation sequencing (NGS)

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

APA (6th Edition):

Lin, J. (2018). Selection of the most informative schemes for multi-locus sequence typing. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0631118-141016

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

Chicago Manual of Style (16th Edition):

Lin, Ji-Wei. “Selection of the most informative schemes for multi-locus sequence typing.” 2018. Thesis, NSYSU. Accessed June 19, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0631118-141016.

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

MLA Handbook (7th Edition):

Lin, Ji-Wei. “Selection of the most informative schemes for multi-locus sequence typing.” 2018. Web. 19 Jun 2019.

Vancouver:

Lin J. Selection of the most informative schemes for multi-locus sequence typing. [Internet] [Thesis]. NSYSU; 2018. [cited 2019 Jun 19]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0631118-141016.

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

Council of Science Editors:

Lin J. Selection of the most informative schemes for multi-locus sequence typing. [Thesis]. NSYSU; 2018. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0631118-141016

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


Victoria University of Wellington

19. Tran, Binh Ngan. Evolutionary Computation for Feature Manipulation in Classification on High-dimensional Data.

Degree: 2018, Victoria University of Wellington

 More and more high-dimensional data appears in machine learning, especially in classification tasks. With thousands of features, these datasets bring challenges to learning algorithms not… (more)

Subjects/Keywords: Evolutionary Computation; Feature selection; Feature construction; Classification; High-dimensional data

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

APA (6th Edition):

Tran, B. N. (2018). Evolutionary Computation for Feature Manipulation in Classification on High-dimensional Data. (Doctoral Dissertation). Victoria University of Wellington. Retrieved from http://hdl.handle.net/10063/7078

Chicago Manual of Style (16th Edition):

Tran, Binh Ngan. “Evolutionary Computation for Feature Manipulation in Classification on High-dimensional Data.” 2018. Doctoral Dissertation, Victoria University of Wellington. Accessed June 19, 2019. http://hdl.handle.net/10063/7078.

MLA Handbook (7th Edition):

Tran, Binh Ngan. “Evolutionary Computation for Feature Manipulation in Classification on High-dimensional Data.” 2018. Web. 19 Jun 2019.

Vancouver:

Tran BN. Evolutionary Computation for Feature Manipulation in Classification on High-dimensional Data. [Internet] [Doctoral dissertation]. Victoria University of Wellington; 2018. [cited 2019 Jun 19]. Available from: http://hdl.handle.net/10063/7078.

Council of Science Editors:

Tran BN. Evolutionary Computation for Feature Manipulation in Classification on High-dimensional Data. [Doctoral Dissertation]. Victoria University of Wellington; 2018. Available from: http://hdl.handle.net/10063/7078


NSYSU

20. Mi, Jung-Chun. Constructing Call Warrant Trading Strategies with Deep Learning in Taiwan.

Degree: Master, Finance, 2018, NSYSU

 This study uses all call warrants from 2003 to 2017 in Taiwan to design trading strategy about Bollinger Bands ,breakouts and moving averages, and then… (more)

Subjects/Keywords: Learning vector quantization; Deep learning; Random forest; Call warrant; Technical analysis; Feature selection

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

APA (6th Edition):

Mi, J. (2018). Constructing Call Warrant Trading Strategies with Deep Learning in Taiwan. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0605118-153511

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

Chicago Manual of Style (16th Edition):

Mi, Jung-Chun. “Constructing Call Warrant Trading Strategies with Deep Learning in Taiwan.” 2018. Thesis, NSYSU. Accessed June 19, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0605118-153511.

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

MLA Handbook (7th Edition):

Mi, Jung-Chun. “Constructing Call Warrant Trading Strategies with Deep Learning in Taiwan.” 2018. Web. 19 Jun 2019.

Vancouver:

Mi J. Constructing Call Warrant Trading Strategies with Deep Learning in Taiwan. [Internet] [Thesis]. NSYSU; 2018. [cited 2019 Jun 19]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0605118-153511.

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

Council of Science Editors:

Mi J. Constructing Call Warrant Trading Strategies with Deep Learning in Taiwan. [Thesis]. NSYSU; 2018. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0605118-153511

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


University of Kansas

21. Zhong, Yi. Feature selection and classification for high-dimensional biological data under cross-validation framework.

Degree: PhD, Biostatistics, 2018, University of Kansas

 This research focuses on using statistical learning methods on high-dimensional biological data analysis. In our implementation of high-dimensional biological data analysis, we primarily utilize the… (more)

Subjects/Keywords: Statistics; cross-validation; feature selection; statistical learning

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

APA (6th Edition):

Zhong, Y. (2018). Feature selection and classification for high-dimensional biological data under cross-validation framework. (Doctoral Dissertation). University of Kansas. Retrieved from http://hdl.handle.net/1808/27072

Chicago Manual of Style (16th Edition):

Zhong, Yi. “Feature selection and classification for high-dimensional biological data under cross-validation framework.” 2018. Doctoral Dissertation, University of Kansas. Accessed June 19, 2019. http://hdl.handle.net/1808/27072.

MLA Handbook (7th Edition):

Zhong, Yi. “Feature selection and classification for high-dimensional biological data under cross-validation framework.” 2018. Web. 19 Jun 2019.

Vancouver:

Zhong Y. Feature selection and classification for high-dimensional biological data under cross-validation framework. [Internet] [Doctoral dissertation]. University of Kansas; 2018. [cited 2019 Jun 19]. Available from: http://hdl.handle.net/1808/27072.

Council of Science Editors:

Zhong Y. Feature selection and classification for high-dimensional biological data under cross-validation framework. [Doctoral Dissertation]. University of Kansas; 2018. Available from: http://hdl.handle.net/1808/27072


University of Cincinnati

22. Guo, Xinyu. Improved Feature-Selection for Classification Problems using Multiple Auto-Encoders.

Degree: PhD, Engineering and Applied Science: Computer Science and Engineering, 2018, University of Cincinnati

 Complex and high-dimensional data such as medical images, sensor measurements, and sounds is oftenlimited. In machine learning, using such datasets to directly train classification algorithms… (more)

Subjects/Keywords: Computer Science; auto-encoder; feature selection; feature learning; deep learning; neuroimaging

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

APA (6th Edition):

Guo, X. (2018). Improved Feature-Selection for Classification Problems using Multiple Auto-Encoders. (Doctoral Dissertation). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1522420335154157

Chicago Manual of Style (16th Edition):

Guo, Xinyu. “Improved Feature-Selection for Classification Problems using Multiple Auto-Encoders.” 2018. Doctoral Dissertation, University of Cincinnati. Accessed June 19, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1522420335154157.

MLA Handbook (7th Edition):

Guo, Xinyu. “Improved Feature-Selection for Classification Problems using Multiple Auto-Encoders.” 2018. Web. 19 Jun 2019.

Vancouver:

Guo X. Improved Feature-Selection for Classification Problems using Multiple Auto-Encoders. [Internet] [Doctoral dissertation]. University of Cincinnati; 2018. [cited 2019 Jun 19]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1522420335154157.

Council of Science Editors:

Guo X. Improved Feature-Selection for Classification Problems using Multiple Auto-Encoders. [Doctoral Dissertation]. University of Cincinnati; 2018. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1522420335154157


University of Ottawa

23. Farah, John. Design and Implementation of an Artificial Intelligence-Driven Gait Phase Recognition System for Orthotic Knee Control .

Degree: 2018, University of Ottawa

 Microprocessor-controlled stance-control knee-ankle-foot orthoses (M-SCKAFO) can have multiple sensors at all lower-limb segments. This causes M-SCKAFO to be bulky and expensive, with complex control systems.… (more)

Subjects/Keywords: Artificial Intelligence; Machine Learning; Gait; Stance Control; Knee ankle Foot Orthosis; Orthosis; Control System; Inertial Measurement Unit; Gait Phase Recognition; Microprocessor; Sensors; Feature Selection

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

APA (6th Edition):

Farah, J. (2018). Design and Implementation of an Artificial Intelligence-Driven Gait Phase Recognition System for Orthotic Knee Control . (Thesis). University of Ottawa. Retrieved from http://hdl.handle.net/10393/37730

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

Chicago Manual of Style (16th Edition):

Farah, John. “Design and Implementation of an Artificial Intelligence-Driven Gait Phase Recognition System for Orthotic Knee Control .” 2018. Thesis, University of Ottawa. Accessed June 19, 2019. http://hdl.handle.net/10393/37730.

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

MLA Handbook (7th Edition):

Farah, John. “Design and Implementation of an Artificial Intelligence-Driven Gait Phase Recognition System for Orthotic Knee Control .” 2018. Web. 19 Jun 2019.

Vancouver:

Farah J. Design and Implementation of an Artificial Intelligence-Driven Gait Phase Recognition System for Orthotic Knee Control . [Internet] [Thesis]. University of Ottawa; 2018. [cited 2019 Jun 19]. Available from: http://hdl.handle.net/10393/37730.

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

Council of Science Editors:

Farah J. Design and Implementation of an Artificial Intelligence-Driven Gait Phase Recognition System for Orthotic Knee Control . [Thesis]. University of Ottawa; 2018. Available from: http://hdl.handle.net/10393/37730

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


University of New Orleans

24. Rastgoufard, Samin. Applications of Artificial Intelligence in Power Systems.

Degree: PhD, Electrical Engineering, 2018, University of New Orleans

  Artificial intelligence tools, which are fast, robust and adaptive can overcome the drawbacks of traditional solutions for several power systems problems. In this work,… (more)

Subjects/Keywords: Aritifical Intelligence (AI), Static Security Evaluation (SSE), Economic Dispatch (ED), Support Vector Machines (SVM), Particle Swarm Optimization (PSO), Feature Selection; Artificial Intelligence and Robotics; Electrical and Electronics; Power and Energy; Theory and Algorithms

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

APA (6th Edition):

Rastgoufard, S. (2018). Applications of Artificial Intelligence in Power Systems. (Doctoral Dissertation). University of New Orleans. Retrieved from https://scholarworks.uno.edu/td/2487

Chicago Manual of Style (16th Edition):

Rastgoufard, Samin. “Applications of Artificial Intelligence in Power Systems.” 2018. Doctoral Dissertation, University of New Orleans. Accessed June 19, 2019. https://scholarworks.uno.edu/td/2487.

MLA Handbook (7th Edition):

Rastgoufard, Samin. “Applications of Artificial Intelligence in Power Systems.” 2018. Web. 19 Jun 2019.

Vancouver:

Rastgoufard S. Applications of Artificial Intelligence in Power Systems. [Internet] [Doctoral dissertation]. University of New Orleans; 2018. [cited 2019 Jun 19]. Available from: https://scholarworks.uno.edu/td/2487.

Council of Science Editors:

Rastgoufard S. Applications of Artificial Intelligence in Power Systems. [Doctoral Dissertation]. University of New Orleans; 2018. Available from: https://scholarworks.uno.edu/td/2487

25. Bonev, Boyan. Feature selection based on information theory.

Degree: 2018, Universidad de Alicante

Subjects/Keywords: Feature selection; Information theory; Pattern recognition; Supervised classification; Selección de características; Teoría de la información; Reconocimiento de patrones; Clasificación supervisada; Ciencia de la Computación e Inteligencia Artificial

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

APA (6th Edition):

Bonev, B. (2018). Feature selection based on information theory. (Thesis). Universidad de Alicante. Retrieved from http://hdl.handle.net/10045/18362

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

Chicago Manual of Style (16th Edition):

Bonev, Boyan. “Feature selection based on information theory.” 2018. Thesis, Universidad de Alicante. Accessed June 19, 2019. http://hdl.handle.net/10045/18362.

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

MLA Handbook (7th Edition):

Bonev, Boyan. “Feature selection based on information theory.” 2018. Web. 19 Jun 2019.

Vancouver:

Bonev B. Feature selection based on information theory. [Internet] [Thesis]. Universidad de Alicante; 2018. [cited 2019 Jun 19]. Available from: http://hdl.handle.net/10045/18362.

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

Council of Science Editors:

Bonev B. Feature selection based on information theory. [Thesis]. Universidad de Alicante; 2018. Available from: http://hdl.handle.net/10045/18362

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

26. Fiérrez, Julián. Increasing the Robustness of Biometric Templates for Dynamic Signature Biometric Systems.

Degree: 2018, Institute of Electrical and Electronics Engineers Inc.

Subjects/Keywords: Biometrics; Dynamic signature; Banking security; Feature selection; Time functions-based system; e-BioSign; Telecomunicaciones

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APA (6th Edition):

Fiérrez, J. (2018). Increasing the Robustness of Biometric Templates for Dynamic Signature Biometric Systems. (Thesis). Institute of Electrical and Electronics Engineers Inc. Retrieved from http://hdl.handle.net/10486/674570

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

Chicago Manual of Style (16th Edition):

Fiérrez, Julián. “Increasing the Robustness of Biometric Templates for Dynamic Signature Biometric Systems.” 2018. Thesis, Institute of Electrical and Electronics Engineers Inc. Accessed June 19, 2019. http://hdl.handle.net/10486/674570.

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

MLA Handbook (7th Edition):

Fiérrez, Julián. “Increasing the Robustness of Biometric Templates for Dynamic Signature Biometric Systems.” 2018. Web. 19 Jun 2019.

Vancouver:

Fiérrez J. Increasing the Robustness of Biometric Templates for Dynamic Signature Biometric Systems. [Internet] [Thesis]. Institute of Electrical and Electronics Engineers Inc.; 2018. [cited 2019 Jun 19]. Available from: http://hdl.handle.net/10486/674570.

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

Council of Science Editors:

Fiérrez J. Increasing the Robustness of Biometric Templates for Dynamic Signature Biometric Systems. [Thesis]. Institute of Electrical and Electronics Engineers Inc.; 2018. Available from: http://hdl.handle.net/10486/674570

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

27. Ricci, Francesco. Parsimonious and Adaptive Contextual Information Acquisition in Recommender Systems.

Degree: 2018, CEUR-WS

Subjects/Keywords: Feature Selection; Decision making; Feature extraction; Context dependent; Context information; Context-aware recommender systems; Contextual factors; Contextual information; Experimental evaluation; Selection methods; System's performance; Recommender systems; Informática

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

APA (6th Edition):

Ricci, F. (2018). Parsimonious and Adaptive Contextual Information Acquisition in Recommender Systems. (Thesis). CEUR-WS. Retrieved from http://hdl.handle.net/10486/675204

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

Chicago Manual of Style (16th Edition):

Ricci, Francesco. “Parsimonious and Adaptive Contextual Information Acquisition in Recommender Systems.” 2018. Thesis, CEUR-WS. Accessed June 19, 2019. http://hdl.handle.net/10486/675204.

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

MLA Handbook (7th Edition):

Ricci, Francesco. “Parsimonious and Adaptive Contextual Information Acquisition in Recommender Systems.” 2018. Web. 19 Jun 2019.

Vancouver:

Ricci F. Parsimonious and Adaptive Contextual Information Acquisition in Recommender Systems. [Internet] [Thesis]. CEUR-WS; 2018. [cited 2019 Jun 19]. Available from: http://hdl.handle.net/10486/675204.

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

Council of Science Editors:

Ricci F. Parsimonious and Adaptive Contextual Information Acquisition in Recommender Systems. [Thesis]. CEUR-WS; 2018. Available from: http://hdl.handle.net/10486/675204

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

28. Ghahramani, Zoubin. A Probabilistic Model for Dirty Multi-task Feature Selection.

Degree: 2018, International Machine Learning Society (IMLS)

Subjects/Keywords: Artificial intelligence; Benchmarking; Learning systems; Statistics; Approximate inference; Expectation; Propagation; Feature selection methods; Latent variable; Learning tasks; Model-based OPC; Predictive performance; Probabilistic modeling; Feature extraction; Informática

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

APA (6th Edition):

Ghahramani, Z. (2018). A Probabilistic Model for Dirty Multi-task Feature Selection. (Thesis). International Machine Learning Society (IMLS). Retrieved from http://hdl.handle.net/10486/674892

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

Chicago Manual of Style (16th Edition):

Ghahramani, Zoubin. “A Probabilistic Model for Dirty Multi-task Feature Selection.” 2018. Thesis, International Machine Learning Society (IMLS). Accessed June 19, 2019. http://hdl.handle.net/10486/674892.

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

MLA Handbook (7th Edition):

Ghahramani, Zoubin. “A Probabilistic Model for Dirty Multi-task Feature Selection.” 2018. Web. 19 Jun 2019.

Vancouver:

Ghahramani Z. A Probabilistic Model for Dirty Multi-task Feature Selection. [Internet] [Thesis]. International Machine Learning Society (IMLS); 2018. [cited 2019 Jun 19]. Available from: http://hdl.handle.net/10486/674892.

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

Council of Science Editors:

Ghahramani Z. A Probabilistic Model for Dirty Multi-task Feature Selection. [Thesis]. International Machine Learning Society (IMLS); 2018. Available from: http://hdl.handle.net/10486/674892

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

29. Cantador, Iván. Time feature selection for identifying active household members.

Degree: 2018, ACM

Subjects/Keywords: Feature selection; Household member identification; Recommender systems; Time features; Informática

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

APA (6th Edition):

Cantador, I. (2018). Time feature selection for identifying active household members. (Thesis). ACM. Retrieved from http://hdl.handle.net/10486/665128

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

Chicago Manual of Style (16th Edition):

Cantador, Iván. “Time feature selection for identifying active household members.” 2018. Thesis, ACM. Accessed June 19, 2019. http://hdl.handle.net/10486/665128.

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

MLA Handbook (7th Edition):

Cantador, Iván. “Time feature selection for identifying active household members.” 2018. Web. 19 Jun 2019.

Vancouver:

Cantador I. Time feature selection for identifying active household members. [Internet] [Thesis]. ACM; 2018. [cited 2019 Jun 19]. Available from: http://hdl.handle.net/10486/665128.

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

Council of Science Editors:

Cantador I. Time feature selection for identifying active household members. [Thesis]. ACM; 2018. Available from: http://hdl.handle.net/10486/665128

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

30. Huerta Rico, Ramón. On the equivalence of Kernel Fisher discriminant analysis and Kernel Quadratic Programming Feature Selection.

Degree: 2018, Elsevier B.V.

Subjects/Keywords: Feature selection; Kernel Fisher discriminant; Kernel methods; Quadratic Programming Feature Selection; Informática

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

APA (6th Edition):

Huerta Rico, R. (2018). On the equivalence of Kernel Fisher discriminant analysis and Kernel Quadratic Programming Feature Selection. (Thesis). Elsevier B.V. Retrieved from http://hdl.handle.net/10486/667689

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

Chicago Manual of Style (16th Edition):

Huerta Rico, Ramón. “On the equivalence of Kernel Fisher discriminant analysis and Kernel Quadratic Programming Feature Selection.” 2018. Thesis, Elsevier B.V. Accessed June 19, 2019. http://hdl.handle.net/10486/667689.

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

MLA Handbook (7th Edition):

Huerta Rico, Ramón. “On the equivalence of Kernel Fisher discriminant analysis and Kernel Quadratic Programming Feature Selection.” 2018. Web. 19 Jun 2019.

Vancouver:

Huerta Rico R. On the equivalence of Kernel Fisher discriminant analysis and Kernel Quadratic Programming Feature Selection. [Internet] [Thesis]. Elsevier B.V.; 2018. [cited 2019 Jun 19]. Available from: http://hdl.handle.net/10486/667689.

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

Council of Science Editors:

Huerta Rico R. On the equivalence of Kernel Fisher discriminant analysis and Kernel Quadratic Programming Feature Selection. [Thesis]. Elsevier B.V.; 2018. Available from: http://hdl.handle.net/10486/667689

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

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