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You searched for subject:(test selection AND classification). Showing records 1 – 30 of 416 total matches.

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1. Verdy, Matthieu. Développement de stratégies de test pour les systèmes de communications millimétriques : Development of test strategies for millimeter communications systems.

Degree: Docteur es, Automatique et productique, 2016, Université Grenoble Alpes (ComUE)

L’objectif de cette thèse est de développer une stratégie de test globale pour réduire le cout du test tout en garantissant une couverture de test(more)

Subjects/Keywords: Test de circuit; Sélection de caractéristiques; Réduction de coût de test; Classification; Circuit testing; Feature selection; Test cost reduction; Classification; 620

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

APA (6th Edition):

Verdy, M. (2016). Développement de stratégies de test pour les systèmes de communications millimétriques : Development of test strategies for millimeter communications systems. (Doctoral Dissertation). Université Grenoble Alpes (ComUE). Retrieved from http://www.theses.fr/2016GREAT078

Chicago Manual of Style (16th Edition):

Verdy, Matthieu. “Développement de stratégies de test pour les systèmes de communications millimétriques : Development of test strategies for millimeter communications systems.” 2016. Doctoral Dissertation, Université Grenoble Alpes (ComUE). Accessed May 08, 2021. http://www.theses.fr/2016GREAT078.

MLA Handbook (7th Edition):

Verdy, Matthieu. “Développement de stratégies de test pour les systèmes de communications millimétriques : Development of test strategies for millimeter communications systems.” 2016. Web. 08 May 2021.

Vancouver:

Verdy M. Développement de stratégies de test pour les systèmes de communications millimétriques : Development of test strategies for millimeter communications systems. [Internet] [Doctoral dissertation]. Université Grenoble Alpes (ComUE); 2016. [cited 2021 May 08]. Available from: http://www.theses.fr/2016GREAT078.

Council of Science Editors:

Verdy M. Développement de stratégies de test pour les systèmes de communications millimétriques : Development of test strategies for millimeter communications systems. [Doctoral Dissertation]. Université Grenoble Alpes (ComUE); 2016. Available from: http://www.theses.fr/2016GREAT078


University of Georgia

2. Brown, Christy. Modification indices for diagnostic classification models.

Degree: 2014, University of Georgia

 Diagnostic classification models (DCMs) have emerged as promising tools for the evaluation of a student’s mastery of the essential skills in a content domain based… (more)

Subjects/Keywords: Diagnostic classification models; Model selection; Q-matrix misspecification; Modification index; One-sided score test

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APA (6th Edition):

Brown, C. (2014). Modification indices for diagnostic classification models. (Thesis). University of Georgia. Retrieved from http://hdl.handle.net/10724/28985

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):

Brown, Christy. “Modification indices for diagnostic classification models.” 2014. Thesis, University of Georgia. Accessed May 08, 2021. http://hdl.handle.net/10724/28985.

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

MLA Handbook (7th Edition):

Brown, Christy. “Modification indices for diagnostic classification models.” 2014. Web. 08 May 2021.

Vancouver:

Brown C. Modification indices for diagnostic classification models. [Internet] [Thesis]. University of Georgia; 2014. [cited 2021 May 08]. Available from: http://hdl.handle.net/10724/28985.

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

Council of Science Editors:

Brown C. Modification indices for diagnostic classification models. [Thesis]. University of Georgia; 2014. Available from: http://hdl.handle.net/10724/28985

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


University of Southern California

3. Rajati, Mohammmad Reza. Evaluation of sequential hypothesis tests for cross validation of learning models using big data.

Degree: MS, Statistics, 2015, University of Southern California

 In this thesis, we examine the application of various sequential hypothesis tests to fast cross validation for model selection. Fast cross validation can be utilized… (more)

Subjects/Keywords: sequential hypothesis testing; cross validation; big data; learning; classification; regression; hyper parameter selection; Cochran test; Friedman test; F test; statistics; non-parametric tests

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APA (6th Edition):

Rajati, M. R. (2015). Evaluation of sequential hypothesis tests for cross validation of learning models using big data. (Masters Thesis). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/587159/rec/2537

Chicago Manual of Style (16th Edition):

Rajati, Mohammmad Reza. “Evaluation of sequential hypothesis tests for cross validation of learning models using big data.” 2015. Masters Thesis, University of Southern California. Accessed May 08, 2021. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/587159/rec/2537.

MLA Handbook (7th Edition):

Rajati, Mohammmad Reza. “Evaluation of sequential hypothesis tests for cross validation of learning models using big data.” 2015. Web. 08 May 2021.

Vancouver:

Rajati MR. Evaluation of sequential hypothesis tests for cross validation of learning models using big data. [Internet] [Masters thesis]. University of Southern California; 2015. [cited 2021 May 08]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/587159/rec/2537.

Council of Science Editors:

Rajati MR. Evaluation of sequential hypothesis tests for cross validation of learning models using big data. [Masters Thesis]. University of Southern California; 2015. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/587159/rec/2537


Colorado State University

4. Bandyopadhyay, Aritra. Mitigating the effect of coincidental correctness in spectrum based fault localization.

Degree: PhD, Computer Science, 2013, Colorado State University

 Coincidentally correct test cases are those that execute faulty program statements but do not result in failures. The presence of such test cases in a… (more)

Subjects/Keywords: software fault localization and debugging; test selection and classification; static and dynamic program analysis; software testing

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APA (6th Edition):

Bandyopadhyay, A. (2013). Mitigating the effect of coincidental correctness in spectrum based fault localization. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/80137

Chicago Manual of Style (16th Edition):

Bandyopadhyay, Aritra. “Mitigating the effect of coincidental correctness in spectrum based fault localization.” 2013. Doctoral Dissertation, Colorado State University. Accessed May 08, 2021. http://hdl.handle.net/10217/80137.

MLA Handbook (7th Edition):

Bandyopadhyay, Aritra. “Mitigating the effect of coincidental correctness in spectrum based fault localization.” 2013. Web. 08 May 2021.

Vancouver:

Bandyopadhyay A. Mitigating the effect of coincidental correctness in spectrum based fault localization. [Internet] [Doctoral dissertation]. Colorado State University; 2013. [cited 2021 May 08]. Available from: http://hdl.handle.net/10217/80137.

Council of Science Editors:

Bandyopadhyay A. Mitigating the effect of coincidental correctness in spectrum based fault localization. [Doctoral Dissertation]. Colorado State University; 2013. Available from: http://hdl.handle.net/10217/80137


Université Catholique de Louvain

5. Gualberto Ferreira Coelho, Frederico. Semi-supervised feature selection.

Degree: 2013, Université Catholique de Louvain

As data acquisition has become relatively easy and inexpensive, data sets are becoming extremely large, both in the number of variables and in the number… (more)

Subjects/Keywords: Machine learning; Feature selection; Classification

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APA (6th Edition):

Gualberto Ferreira Coelho, F. (2013). Semi-supervised feature selection. (Thesis). Université Catholique de Louvain. Retrieved from http://hdl.handle.net/2078.1/128255

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):

Gualberto Ferreira Coelho, Frederico. “Semi-supervised feature selection.” 2013. Thesis, Université Catholique de Louvain. Accessed May 08, 2021. http://hdl.handle.net/2078.1/128255.

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

MLA Handbook (7th Edition):

Gualberto Ferreira Coelho, Frederico. “Semi-supervised feature selection.” 2013. Web. 08 May 2021.

Vancouver:

Gualberto Ferreira Coelho F. Semi-supervised feature selection. [Internet] [Thesis]. Université Catholique de Louvain; 2013. [cited 2021 May 08]. Available from: http://hdl.handle.net/2078.1/128255.

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

Council of Science Editors:

Gualberto Ferreira Coelho F. Semi-supervised feature selection. [Thesis]. Université Catholique de Louvain; 2013. Available from: http://hdl.handle.net/2078.1/128255

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

6. Wei, Jiawei. Secondary Analysis of Case-Control Studies in Genomic Contexts.

Degree: PhD, Statistics, 2011, Texas A&M University

 This dissertation consists of five independent projects. In each project, a novel statistical method was developed to address a practical problem encountered in genomic contexts.… (more)

Subjects/Keywords: Semiparametric Regression; Case-Control; Score Test; Model Selection; Classification

…viii CHAPTER Page 1. Selection of the Smoothing Parameters in Simulation Studies… …2. Selection of the Numbers of the Principle Components in Simulation Studies… …3. Model Selection in the Rreal Data Example . . . . D. Discussion… …VI . . 56 . . . . . . 60 60 62 PERMUTATION TEST FOR MICROARRAYS: COLONIC TUMORIGENESIS… …1. Cross-validated Permutation Test (CPT) . . . . . 2. Cross-validated within… 

Page 1 Page 2 Page 3 Page 4 Page 5 Page 6 Page 7

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APA (6th Edition):

Wei, J. (2011). Secondary Analysis of Case-Control Studies in Genomic Contexts. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8269

Chicago Manual of Style (16th Edition):

Wei, Jiawei. “Secondary Analysis of Case-Control Studies in Genomic Contexts.” 2011. Doctoral Dissertation, Texas A&M University. Accessed May 08, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8269.

MLA Handbook (7th Edition):

Wei, Jiawei. “Secondary Analysis of Case-Control Studies in Genomic Contexts.” 2011. Web. 08 May 2021.

Vancouver:

Wei J. Secondary Analysis of Case-Control Studies in Genomic Contexts. [Internet] [Doctoral dissertation]. Texas A&M University; 2011. [cited 2021 May 08]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8269.

Council of Science Editors:

Wei J. Secondary Analysis of Case-Control Studies in Genomic Contexts. [Doctoral Dissertation]. Texas A&M University; 2011. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8269


Delft University of Technology

7. Razoux Schultz, Lex (author). Distance Based Source Domain Selection for Automated Sentiment Classification.

Degree: 2018, Delft University of Technology

Automated Sentiment Classification (SC) on short text fragments has been an upcoming field of research. Different machine learning techniques and word representation models have proven… (more)

Subjects/Keywords: sentiment analysis; sentiment classification; domain adaptation; source selection; domain selection

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APA (6th Edition):

Razoux Schultz, L. (. (2018). Distance Based Source Domain Selection for Automated Sentiment Classification. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:bc430a45-3377-40de-9408-428b39b4f196

Chicago Manual of Style (16th Edition):

Razoux Schultz, Lex (author). “Distance Based Source Domain Selection for Automated Sentiment Classification.” 2018. Masters Thesis, Delft University of Technology. Accessed May 08, 2021. http://resolver.tudelft.nl/uuid:bc430a45-3377-40de-9408-428b39b4f196.

MLA Handbook (7th Edition):

Razoux Schultz, Lex (author). “Distance Based Source Domain Selection for Automated Sentiment Classification.” 2018. Web. 08 May 2021.

Vancouver:

Razoux Schultz L(. Distance Based Source Domain Selection for Automated Sentiment Classification. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 May 08]. Available from: http://resolver.tudelft.nl/uuid:bc430a45-3377-40de-9408-428b39b4f196.

Council of Science Editors:

Razoux Schultz L(. Distance Based Source Domain Selection for Automated Sentiment Classification. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:bc430a45-3377-40de-9408-428b39b4f196


Rhodes University

8. De Wet, Leigh-Ann Robynne. Pollinator mediated selection in Pelargonium reniforme Curtis (Geraniaceae) : patterns and process.

Degree: Faculty of Science, Botany, 2013, Rhodes University

Pelargonium reniforme is currently divided into two subspecies, P. reniforme subsp. reniforme and P. reniforme subsp. velutinum. The species falls into section Reniformia along with… (more)

Subjects/Keywords: Pelargoniums  – Classification; Pelargoniums  – Pollen; Pelargoniums  – Selection

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APA (6th Edition):

De Wet, L. R. (2013). Pollinator mediated selection in Pelargonium reniforme Curtis (Geraniaceae) : patterns and process. (Thesis). Rhodes University. Retrieved from http://hdl.handle.net/10962/d1008185

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):

De Wet, Leigh-Ann Robynne. “Pollinator mediated selection in Pelargonium reniforme Curtis (Geraniaceae) : patterns and process.” 2013. Thesis, Rhodes University. Accessed May 08, 2021. http://hdl.handle.net/10962/d1008185.

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

MLA Handbook (7th Edition):

De Wet, Leigh-Ann Robynne. “Pollinator mediated selection in Pelargonium reniforme Curtis (Geraniaceae) : patterns and process.” 2013. Web. 08 May 2021.

Vancouver:

De Wet LR. Pollinator mediated selection in Pelargonium reniforme Curtis (Geraniaceae) : patterns and process. [Internet] [Thesis]. Rhodes University; 2013. [cited 2021 May 08]. Available from: http://hdl.handle.net/10962/d1008185.

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

Council of Science Editors:

De Wet LR. Pollinator mediated selection in Pelargonium reniforme Curtis (Geraniaceae) : patterns and process. [Thesis]. Rhodes University; 2013. Available from: http://hdl.handle.net/10962/d1008185

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

9. Gui, Tian. A Pairwise Feature Selection Method For Gene Data Using Information Gain.

Degree: M.S. in Engineering Science, Computer and Information Science, 2014, University of Mississippi

 The current technical practice for doing classification has limitations when using gene expression microarray data. For example, the robustness of top scoring pairs does not… (more)

Subjects/Keywords: Classification; Feature Selection; Gene Expression; Bioinformatics

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APA (6th Edition):

Gui, T. (2014). A Pairwise Feature Selection Method For Gene Data Using Information Gain. (Thesis). University of Mississippi. Retrieved from https://egrove.olemiss.edu/etd/943

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):

Gui, Tian. “A Pairwise Feature Selection Method For Gene Data Using Information Gain.” 2014. Thesis, University of Mississippi. Accessed May 08, 2021. https://egrove.olemiss.edu/etd/943.

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

MLA Handbook (7th Edition):

Gui, Tian. “A Pairwise Feature Selection Method For Gene Data Using Information Gain.” 2014. Web. 08 May 2021.

Vancouver:

Gui T. A Pairwise Feature Selection Method For Gene Data Using Information Gain. [Internet] [Thesis]. University of Mississippi; 2014. [cited 2021 May 08]. Available from: https://egrove.olemiss.edu/etd/943.

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

Council of Science Editors:

Gui T. A Pairwise Feature Selection Method For Gene Data Using Information Gain. [Thesis]. University of Mississippi; 2014. Available from: https://egrove.olemiss.edu/etd/943

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


University of Sydney

10. Pham, Thuy Thi. Automated Classification for Biomedical Data: Machine Learning Approaches for Subject-Independent Settings .

Degree: 2017, University of Sydney

 This thesis advocates two main factors to improve subject-independent automated classification techniques: utilizing better feature extraction, and a more efficient model of classification. Supervised techniques… (more)

Subjects/Keywords: Subject-independent; automated classification; feature selection; anomaly

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APA (6th Edition):

Pham, T. T. (2017). Automated Classification for Biomedical Data: Machine Learning Approaches for Subject-Independent Settings . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/17177

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):

Pham, Thuy Thi. “Automated Classification for Biomedical Data: Machine Learning Approaches for Subject-Independent Settings .” 2017. Thesis, University of Sydney. Accessed May 08, 2021. http://hdl.handle.net/2123/17177.

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

MLA Handbook (7th Edition):

Pham, Thuy Thi. “Automated Classification for Biomedical Data: Machine Learning Approaches for Subject-Independent Settings .” 2017. Web. 08 May 2021.

Vancouver:

Pham TT. Automated Classification for Biomedical Data: Machine Learning Approaches for Subject-Independent Settings . [Internet] [Thesis]. University of Sydney; 2017. [cited 2021 May 08]. Available from: http://hdl.handle.net/2123/17177.

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

Council of Science Editors:

Pham TT. Automated Classification for Biomedical Data: Machine Learning Approaches for Subject-Independent Settings . [Thesis]. University of Sydney; 2017. Available from: http://hdl.handle.net/2123/17177

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

11. Ndour, Cheikh. Modélisation statistique de la mortalité maternelle et néonatale pour l'aide à la planification et à la gestion des services de santé en Afrique Sub-Saharienne : Statistical modeling of maternal and neonatal mortality for help in planning and management of health services in sub-Saharan Africa.

Degree: Docteur es, Mathématiques appliquées, 2014, Pau

L'objectif de cette thèse est de proposer une méthodologie statistique permettant de formuler une règle de classement capable de surmonter les difficultés qui se présentent… (more)

Subjects/Keywords: Apprentissage statistique; Classement; Données déséquilibrées; Estimation Bayésienne empirique; Mortalité maternelle; Profils; Règles d'association; Sélection de profils; Test d'hypothèse; Association rules; Classification; Empirical Bayesian estimation; Hypothesis testing; Maternal mortality; Patterns; Selection patterns; Statistical learning; Unbalanced data

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APA (6th Edition):

Ndour, C. (2014). Modélisation statistique de la mortalité maternelle et néonatale pour l'aide à la planification et à la gestion des services de santé en Afrique Sub-Saharienne : Statistical modeling of maternal and neonatal mortality for help in planning and management of health services in sub-Saharan Africa. (Doctoral Dissertation). Pau. Retrieved from http://www.theses.fr/2014PAUU3007

Chicago Manual of Style (16th Edition):

Ndour, Cheikh. “Modélisation statistique de la mortalité maternelle et néonatale pour l'aide à la planification et à la gestion des services de santé en Afrique Sub-Saharienne : Statistical modeling of maternal and neonatal mortality for help in planning and management of health services in sub-Saharan Africa.” 2014. Doctoral Dissertation, Pau. Accessed May 08, 2021. http://www.theses.fr/2014PAUU3007.

MLA Handbook (7th Edition):

Ndour, Cheikh. “Modélisation statistique de la mortalité maternelle et néonatale pour l'aide à la planification et à la gestion des services de santé en Afrique Sub-Saharienne : Statistical modeling of maternal and neonatal mortality for help in planning and management of health services in sub-Saharan Africa.” 2014. Web. 08 May 2021.

Vancouver:

Ndour C. Modélisation statistique de la mortalité maternelle et néonatale pour l'aide à la planification et à la gestion des services de santé en Afrique Sub-Saharienne : Statistical modeling of maternal and neonatal mortality for help in planning and management of health services in sub-Saharan Africa. [Internet] [Doctoral dissertation]. Pau; 2014. [cited 2021 May 08]. Available from: http://www.theses.fr/2014PAUU3007.

Council of Science Editors:

Ndour C. Modélisation statistique de la mortalité maternelle et néonatale pour l'aide à la planification et à la gestion des services de santé en Afrique Sub-Saharienne : Statistical modeling of maternal and neonatal mortality for help in planning and management of health services in sub-Saharan Africa. [Doctoral Dissertation]. Pau; 2014. Available from: http://www.theses.fr/2014PAUU3007


University of South Florida

12. Canul Reich, Juana. An Iterative Feature Perturbation Method for Gene Selection from Microarray Data.

Degree: 2010, University of South Florida

 Gene expression microarray datasets often consist of a limited number of samples relative to a large number of expression measurements, usually on the order of… (more)

Subjects/Keywords: IFP; feature selection; classification; t-test; data mining; SVM-RFE; SVM; American Studies; Arts and Humanities

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APA (6th Edition):

Canul Reich, J. (2010). An Iterative Feature Perturbation Method for Gene Selection from Microarray Data. (Thesis). University of South Florida. Retrieved from https://scholarcommons.usf.edu/etd/1588

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):

Canul Reich, Juana. “An Iterative Feature Perturbation Method for Gene Selection from Microarray Data.” 2010. Thesis, University of South Florida. Accessed May 08, 2021. https://scholarcommons.usf.edu/etd/1588.

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

MLA Handbook (7th Edition):

Canul Reich, Juana. “An Iterative Feature Perturbation Method for Gene Selection from Microarray Data.” 2010. Web. 08 May 2021.

Vancouver:

Canul Reich J. An Iterative Feature Perturbation Method for Gene Selection from Microarray Data. [Internet] [Thesis]. University of South Florida; 2010. [cited 2021 May 08]. Available from: https://scholarcommons.usf.edu/etd/1588.

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

Council of Science Editors:

Canul Reich J. An Iterative Feature Perturbation Method for Gene Selection from Microarray Data. [Thesis]. University of South Florida; 2010. Available from: https://scholarcommons.usf.edu/etd/1588

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

13. Xiao, Xinhua. Automated Defect Recognition in Digital Radiography.

Degree: PhD, Engineering and Applied Science: Electrical Engineering, 2015, University of Cincinnati

 Digital radiography has been widely used for non-destructive testing in industrial production. An example is the inspection of industrial parts like turbine blades of jet… (more)

Subjects/Keywords: Electrical Engineering; reference image selection; statistical test; image classification; turbine blade; model adaptation; X-ray

…powerful than t-test but more safe for use. To compare classification rates (sensitivity… …39 5.3 McNemar’s Test… …47 Table 5.6 McNemar’s test for model sets with 1, 2, 3, 4, 5, and 10 worst negative… …48 Table 5.8 McNemar’s test for model sets with 1, 3, 5, 10, and 20 positive defective… …18 Figure 3.3 Framework of the model selection problem of ADR… 

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APA (6th Edition):

Xiao, X. (2015). Automated Defect Recognition in Digital Radiography. (Doctoral Dissertation). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439309683

Chicago Manual of Style (16th Edition):

Xiao, Xinhua. “Automated Defect Recognition in Digital Radiography.” 2015. Doctoral Dissertation, University of Cincinnati. Accessed May 08, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439309683.

MLA Handbook (7th Edition):

Xiao, Xinhua. “Automated Defect Recognition in Digital Radiography.” 2015. Web. 08 May 2021.

Vancouver:

Xiao X. Automated Defect Recognition in Digital Radiography. [Internet] [Doctoral dissertation]. University of Cincinnati; 2015. [cited 2021 May 08]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439309683.

Council of Science Editors:

Xiao X. Automated Defect Recognition in Digital Radiography. [Doctoral Dissertation]. University of Cincinnati; 2015. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439309683

14. Lyon, Robert James. Why Are Pulsars Hard To Find?.

Degree: 2016, University of Manchester

 Searches for pulsars during the past fifty years, have been characterised by two problems making their discovery difficult: i) an increasing volume of data to… (more)

Subjects/Keywords: Pulsar; Search; Classification; Candidate Selection; Stream classification; Imbalanced Learning; SKA

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APA (6th Edition):

Lyon, R. J. (2016). Why Are Pulsars Hard To Find?. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:305203

Chicago Manual of Style (16th Edition):

Lyon, Robert James. “Why Are Pulsars Hard To Find?.” 2016. Doctoral Dissertation, University of Manchester. Accessed May 08, 2021. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:305203.

MLA Handbook (7th Edition):

Lyon, Robert James. “Why Are Pulsars Hard To Find?.” 2016. Web. 08 May 2021.

Vancouver:

Lyon RJ. Why Are Pulsars Hard To Find?. [Internet] [Doctoral dissertation]. University of Manchester; 2016. [cited 2021 May 08]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:305203.

Council of Science Editors:

Lyon RJ. Why Are Pulsars Hard To Find?. [Doctoral Dissertation]. University of Manchester; 2016. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:305203

15. Lyon, Robert James. Why are pulsars hard to find?.

Degree: PhD, 2016, University of Manchester

 Searches for pulsars during the past fifty years, have been characterised by two problems making their discovery difficult: i) an increasing volume of data to… (more)

Subjects/Keywords: 523.8; Pulsar; Search; Classification; Candidate Selection; Stream classification; Imbalanced Learning; SKA

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

APA (6th Edition):

Lyon, R. J. (2016). Why are pulsars hard to find?. (Doctoral Dissertation). University of Manchester. Retrieved from https://www.research.manchester.ac.uk/portal/en/theses/why-are-pulsars-hard-to-find(f15226ec-355d-4794-b2b8-e0a8e793948e).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.706255

Chicago Manual of Style (16th Edition):

Lyon, Robert James. “Why are pulsars hard to find?.” 2016. Doctoral Dissertation, University of Manchester. Accessed May 08, 2021. https://www.research.manchester.ac.uk/portal/en/theses/why-are-pulsars-hard-to-find(f15226ec-355d-4794-b2b8-e0a8e793948e).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.706255.

MLA Handbook (7th Edition):

Lyon, Robert James. “Why are pulsars hard to find?.” 2016. Web. 08 May 2021.

Vancouver:

Lyon RJ. Why are pulsars hard to find?. [Internet] [Doctoral dissertation]. University of Manchester; 2016. [cited 2021 May 08]. Available from: https://www.research.manchester.ac.uk/portal/en/theses/why-are-pulsars-hard-to-find(f15226ec-355d-4794-b2b8-e0a8e793948e).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.706255.

Council of Science Editors:

Lyon RJ. Why are pulsars hard to find?. [Doctoral Dissertation]. University of Manchester; 2016. Available from: https://www.research.manchester.ac.uk/portal/en/theses/why-are-pulsars-hard-to-find(f15226ec-355d-4794-b2b8-e0a8e793948e).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.706255


KTH

16. Anette, Kniberg. A Benchmark of Prevalent Feature Selection Algorithms on a Diverse Set of Classification Problems.

Degree: Biomedical Engineering and Health Systems, 2018, KTH

Feature selection is the process of automatically selecting important features from data. It is an essential part of machine learning, artificial intelligence, data mining,… (more)

Subjects/Keywords: feature selection; variable selection; attribute selection; machine learning; data mining; benchmark; classification; variabelselektion; maskininlärning; datautvinning; klassificering; Medical Engineering; Medicinteknik

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APA (6th Edition):

Anette, K. (2018). A Benchmark of Prevalent Feature Selection Algorithms on a Diverse Set of Classification Problems. (Thesis). KTH. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-228614

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):

Anette, Kniberg. “A Benchmark of Prevalent Feature Selection Algorithms on a Diverse Set of Classification Problems.” 2018. Thesis, KTH. Accessed May 08, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-228614.

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

MLA Handbook (7th Edition):

Anette, Kniberg. “A Benchmark of Prevalent Feature Selection Algorithms on a Diverse Set of Classification Problems.” 2018. Web. 08 May 2021.

Vancouver:

Anette K. A Benchmark of Prevalent Feature Selection Algorithms on a Diverse Set of Classification Problems. [Internet] [Thesis]. KTH; 2018. [cited 2021 May 08]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-228614.

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

Council of Science Editors:

Anette K. A Benchmark of Prevalent Feature Selection Algorithms on a Diverse Set of Classification Problems. [Thesis]. KTH; 2018. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-228614

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

17. Truong Hoang, Vinh. Multi color space LBP-based feature selection for texture classification : Sélection d'attributs multi-espace à partir de motifs binaires locaux pour la classification de textures couleur.

Degree: Docteur es, Traitement du signal et des images, 2018, Littoral

L'analyse de texture a été largement étudiée dans la littérature et une grande variété de descripteurs de texture ont été proposés. Parmi ceux-ci, les motifs… (more)

Subjects/Keywords: Classification de textures; Espaces couleur; Opérateur LBP; Sélection d'attributs; Sélection d'histogramme; Sélection de bins; Apprentissage supervisé; Texture classification; Color spaces; LBP operator; Feature selection; Histogram selection; Bin selection; Supervised learning

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

APA (6th Edition):

Truong Hoang, V. (2018). Multi color space LBP-based feature selection for texture classification : Sélection d'attributs multi-espace à partir de motifs binaires locaux pour la classification de textures couleur. (Doctoral Dissertation). Littoral. Retrieved from http://www.theses.fr/2018DUNK0468

Chicago Manual of Style (16th Edition):

Truong Hoang, Vinh. “Multi color space LBP-based feature selection for texture classification : Sélection d'attributs multi-espace à partir de motifs binaires locaux pour la classification de textures couleur.” 2018. Doctoral Dissertation, Littoral. Accessed May 08, 2021. http://www.theses.fr/2018DUNK0468.

MLA Handbook (7th Edition):

Truong Hoang, Vinh. “Multi color space LBP-based feature selection for texture classification : Sélection d'attributs multi-espace à partir de motifs binaires locaux pour la classification de textures couleur.” 2018. Web. 08 May 2021.

Vancouver:

Truong Hoang V. Multi color space LBP-based feature selection for texture classification : Sélection d'attributs multi-espace à partir de motifs binaires locaux pour la classification de textures couleur. [Internet] [Doctoral dissertation]. Littoral; 2018. [cited 2021 May 08]. Available from: http://www.theses.fr/2018DUNK0468.

Council of Science Editors:

Truong Hoang V. Multi color space LBP-based feature selection for texture classification : Sélection d'attributs multi-espace à partir de motifs binaires locaux pour la classification de textures couleur. [Doctoral Dissertation]. Littoral; 2018. Available from: http://www.theses.fr/2018DUNK0468


University of Utah

18. Dudley, Kenneth. Mapping species across multiple dates of hyperspectral imagery using iterative endmember selection and multiple endmember spectral mixture analysis.

Degree: MS, Geography, 2014, University of Utah

 Vegetation phenology results in seasonal changes in spectral reflectance. Phenology is often underutilized in hyperspectral vegetation mapping due to a lack of repeat imagery of… (more)

Subjects/Keywords: Endmember selection; Hyperspectral time series; HyspIRI; MESMA; Species classification; Vegetation phenology

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APA (6th Edition):

Dudley, K. (2014). Mapping species across multiple dates of hyperspectral imagery using iterative endmember selection and multiple endmember spectral mixture analysis. (Masters Thesis). University of Utah. Retrieved from http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/3299/rec/1526

Chicago Manual of Style (16th Edition):

Dudley, Kenneth. “Mapping species across multiple dates of hyperspectral imagery using iterative endmember selection and multiple endmember spectral mixture analysis.” 2014. Masters Thesis, University of Utah. Accessed May 08, 2021. http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/3299/rec/1526.

MLA Handbook (7th Edition):

Dudley, Kenneth. “Mapping species across multiple dates of hyperspectral imagery using iterative endmember selection and multiple endmember spectral mixture analysis.” 2014. Web. 08 May 2021.

Vancouver:

Dudley K. Mapping species across multiple dates of hyperspectral imagery using iterative endmember selection and multiple endmember spectral mixture analysis. [Internet] [Masters thesis]. University of Utah; 2014. [cited 2021 May 08]. Available from: http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/3299/rec/1526.

Council of Science Editors:

Dudley K. Mapping species across multiple dates of hyperspectral imagery using iterative endmember selection and multiple endmember spectral mixture analysis. [Masters Thesis]. University of Utah; 2014. Available from: http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/3299/rec/1526


Rochester Institute of Technology

19. Syed, Abdul Haleem. Segmentation and Classification of Remotely Sensed Images: Object-Based Image Analysis.

Degree: PhD, Chester F. Carlson Center for Imaging Science (COS), 2015, Rochester Institute of Technology

  Land-use-and-land-cover (LULC) mapping is crucial in precision agriculture, environmental monitoring, disaster response, and military applications. The demand for improved and more accurate LULC maps… (more)

Subjects/Keywords: Hierarchical segmentation; Scale selection; Scale space analysis; Supervised classification

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

APA (6th Edition):

Syed, A. H. (2015). Segmentation and Classification of Remotely Sensed Images: Object-Based Image Analysis. (Doctoral Dissertation). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/8823

Chicago Manual of Style (16th Edition):

Syed, Abdul Haleem. “Segmentation and Classification of Remotely Sensed Images: Object-Based Image Analysis.” 2015. Doctoral Dissertation, Rochester Institute of Technology. Accessed May 08, 2021. https://scholarworks.rit.edu/theses/8823.

MLA Handbook (7th Edition):

Syed, Abdul Haleem. “Segmentation and Classification of Remotely Sensed Images: Object-Based Image Analysis.” 2015. Web. 08 May 2021.

Vancouver:

Syed AH. Segmentation and Classification of Remotely Sensed Images: Object-Based Image Analysis. [Internet] [Doctoral dissertation]. Rochester Institute of Technology; 2015. [cited 2021 May 08]. Available from: https://scholarworks.rit.edu/theses/8823.

Council of Science Editors:

Syed AH. Segmentation and Classification of Remotely Sensed Images: Object-Based Image Analysis. [Doctoral Dissertation]. Rochester Institute of Technology; 2015. Available from: https://scholarworks.rit.edu/theses/8823


Queens University

20. Rahman, Quazi. Computational Methods for Identifying Hypertrophic Cardiomyopathy using 12-lead ECG .

Degree: Computing, 2016, Queens University

 Hypertrophic cardiomyopathy (HCM) is a cardiovascular disease where the heart muscle is partially thickened and blood flow is - potentially fatally - obstructed. It is… (more)

Subjects/Keywords: Feature selection ; Hypertrophic cardiomyopathy ; ECG Classification ; Electrocardiography ; Machine learning

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APA (6th Edition):

Rahman, Q. (2016). Computational Methods for Identifying Hypertrophic Cardiomyopathy using 12-lead ECG . (Thesis). Queens University. Retrieved from http://hdl.handle.net/1974/14506

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):

Rahman, Quazi. “Computational Methods for Identifying Hypertrophic Cardiomyopathy using 12-lead ECG .” 2016. Thesis, Queens University. Accessed May 08, 2021. http://hdl.handle.net/1974/14506.

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

MLA Handbook (7th Edition):

Rahman, Quazi. “Computational Methods for Identifying Hypertrophic Cardiomyopathy using 12-lead ECG .” 2016. Web. 08 May 2021.

Vancouver:

Rahman Q. Computational Methods for Identifying Hypertrophic Cardiomyopathy using 12-lead ECG . [Internet] [Thesis]. Queens University; 2016. [cited 2021 May 08]. Available from: http://hdl.handle.net/1974/14506.

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

Council of Science Editors:

Rahman Q. Computational Methods for Identifying Hypertrophic Cardiomyopathy using 12-lead ECG . [Thesis]. Queens University; 2016. Available from: http://hdl.handle.net/1974/14506

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


North Carolina State University

21. Huang, Lingkang. Variable Selection in Multiclass Support Vector Machine and Applications in Genomic Data Analysis.

Degree: PhD, Statistics, 2009, North Carolina State University

 Microarray techniques provide new insights into cancer diagnosis using gene expression profiles. Molecular diagnosis based on high-throughput genomic data sets presents major challenge due to… (more)

Subjects/Keywords: multi-class classification; support vector machine; microarray; variable selection

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

APA (6th Edition):

Huang, L. (2009). Variable Selection in Multiclass Support Vector Machine and Applications in Genomic Data Analysis. (Doctoral Dissertation). North Carolina State University. Retrieved from http://www.lib.ncsu.edu/resolver/1840.16/5240

Chicago Manual of Style (16th Edition):

Huang, Lingkang. “Variable Selection in Multiclass Support Vector Machine and Applications in Genomic Data Analysis.” 2009. Doctoral Dissertation, North Carolina State University. Accessed May 08, 2021. http://www.lib.ncsu.edu/resolver/1840.16/5240.

MLA Handbook (7th Edition):

Huang, Lingkang. “Variable Selection in Multiclass Support Vector Machine and Applications in Genomic Data Analysis.” 2009. Web. 08 May 2021.

Vancouver:

Huang L. Variable Selection in Multiclass Support Vector Machine and Applications in Genomic Data Analysis. [Internet] [Doctoral dissertation]. North Carolina State University; 2009. [cited 2021 May 08]. Available from: http://www.lib.ncsu.edu/resolver/1840.16/5240.

Council of Science Editors:

Huang L. Variable Selection in Multiclass Support Vector Machine and Applications in Genomic Data Analysis. [Doctoral Dissertation]. North Carolina State University; 2009. Available from: http://www.lib.ncsu.edu/resolver/1840.16/5240


Victoria University of Wellington

22. 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 (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 May 08, 2021. 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. 08 May 2021.

Vancouver:

Tran BN. Evolutionary Computation for Feature Manipulation in Classification on High-dimensional Data. [Internet] [Doctoral dissertation]. Victoria University of Wellington; 2018. [cited 2021 May 08]. 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


University of Guelph

23. Petrcich, William. Dimensionality Reduction in the Creation of Classifiers and the Effects of Correlation, Cluster Overlap, and Modelling Assumptions.

Degree: MS, Department of Mathematics and Statistics, 2011, University of Guelph

 Discriminant analysis and random forests are used to create models for classification. The number of variables to be tested for inclusion in a model can… (more)

Subjects/Keywords: food authentication; classification; variable selection; BIC; mclust; random forests; clustvarsel

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APA (6th Edition):

Petrcich, W. (2011). Dimensionality Reduction in the Creation of Classifiers and the Effects of Correlation, Cluster Overlap, and Modelling Assumptions. (Masters Thesis). University of Guelph. Retrieved from https://atrium.lib.uoguelph.ca/xmlui/handle/10214/2933

Chicago Manual of Style (16th Edition):

Petrcich, William. “Dimensionality Reduction in the Creation of Classifiers and the Effects of Correlation, Cluster Overlap, and Modelling Assumptions.” 2011. Masters Thesis, University of Guelph. Accessed May 08, 2021. https://atrium.lib.uoguelph.ca/xmlui/handle/10214/2933.

MLA Handbook (7th Edition):

Petrcich, William. “Dimensionality Reduction in the Creation of Classifiers and the Effects of Correlation, Cluster Overlap, and Modelling Assumptions.” 2011. Web. 08 May 2021.

Vancouver:

Petrcich W. Dimensionality Reduction in the Creation of Classifiers and the Effects of Correlation, Cluster Overlap, and Modelling Assumptions. [Internet] [Masters thesis]. University of Guelph; 2011. [cited 2021 May 08]. Available from: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/2933.

Council of Science Editors:

Petrcich W. Dimensionality Reduction in the Creation of Classifiers and the Effects of Correlation, Cluster Overlap, and Modelling Assumptions. [Masters Thesis]. University of Guelph; 2011. Available from: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/2933


University of Guelph

24. ELmahgiubi, Mohammed. An Efficient Framework for Automatic Algorithm Selection using Meta-Learning.

Degree: Master of Applied Science, School of Engineering, 2016, University of Guelph

 With the unprecedented growth of Information and communication technology (ICT) industry, core networking devices become highly stringent elements of the network due to the increase… (more)

Subjects/Keywords: Machine Learning; Meta-Learning; Algorithm Selection; Packet Classification

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APA (6th Edition):

ELmahgiubi, M. (2016). An Efficient Framework for Automatic Algorithm Selection using Meta-Learning. (Masters Thesis). University of Guelph. Retrieved from https://atrium.lib.uoguelph.ca/xmlui/handle/10214/9972

Chicago Manual of Style (16th Edition):

ELmahgiubi, Mohammed. “An Efficient Framework for Automatic Algorithm Selection using Meta-Learning.” 2016. Masters Thesis, University of Guelph. Accessed May 08, 2021. https://atrium.lib.uoguelph.ca/xmlui/handle/10214/9972.

MLA Handbook (7th Edition):

ELmahgiubi, Mohammed. “An Efficient Framework for Automatic Algorithm Selection using Meta-Learning.” 2016. Web. 08 May 2021.

Vancouver:

ELmahgiubi M. An Efficient Framework for Automatic Algorithm Selection using Meta-Learning. [Internet] [Masters thesis]. University of Guelph; 2016. [cited 2021 May 08]. Available from: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/9972.

Council of Science Editors:

ELmahgiubi M. An Efficient Framework for Automatic Algorithm Selection using Meta-Learning. [Masters Thesis]. University of Guelph; 2016. Available from: https://atrium.lib.uoguelph.ca/xmlui/handle/10214/9972


Tampere University

25. Bartaula, Jyoti Prasad. Classification Of Lymph Node Metastases In Breast Cancer With Features From Tissue Images Using Machine Learning Techniques .

Degree: 2017, Tampere University

 Determining the metastatic involvement of lymph node is very crucial in designing the treatment plans in breast cancer. Traditional way of detecting the lymph node… (more)

Subjects/Keywords: Lymph node metastasis; Breast cancer; Feature selection; Classification

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APA (6th Edition):

Bartaula, J. P. (2017). Classification Of Lymph Node Metastases In Breast Cancer With Features From Tissue Images Using Machine Learning Techniques . (Masters Thesis). Tampere University. Retrieved from https://trepo.tuni.fi/handle/10024/101726

Chicago Manual of Style (16th Edition):

Bartaula, Jyoti Prasad. “Classification Of Lymph Node Metastases In Breast Cancer With Features From Tissue Images Using Machine Learning Techniques .” 2017. Masters Thesis, Tampere University. Accessed May 08, 2021. https://trepo.tuni.fi/handle/10024/101726.

MLA Handbook (7th Edition):

Bartaula, Jyoti Prasad. “Classification Of Lymph Node Metastases In Breast Cancer With Features From Tissue Images Using Machine Learning Techniques .” 2017. Web. 08 May 2021.

Vancouver:

Bartaula JP. Classification Of Lymph Node Metastases In Breast Cancer With Features From Tissue Images Using Machine Learning Techniques . [Internet] [Masters thesis]. Tampere University; 2017. [cited 2021 May 08]. Available from: https://trepo.tuni.fi/handle/10024/101726.

Council of Science Editors:

Bartaula JP. Classification Of Lymph Node Metastases In Breast Cancer With Features From Tissue Images Using Machine Learning Techniques . [Masters Thesis]. Tampere University; 2017. Available from: https://trepo.tuni.fi/handle/10024/101726


University of Houston

26. Ocegueda-Hernandez, Francisco 1978-. AN EMPIRICAL STUDY OF THE SUITABILITY OF CLASS DECOMPOSITION FOR LINEAR CLASSIFIERS.

Degree: PhD, Computer Science, 2012, University of Houston

 The presence of sub-classes within a data sample suggests a class decomposition approach to classification, where each subclass is treated as a new class. Class… (more)

Subjects/Keywords: Meta-learning; Model Selection in Classification; Computer science

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APA (6th Edition):

Ocegueda-Hernandez, F. 1. (2012). AN EMPIRICAL STUDY OF THE SUITABILITY OF CLASS DECOMPOSITION FOR LINEAR CLASSIFIERS. (Doctoral Dissertation). University of Houston. Retrieved from http://hdl.handle.net/10657/798

Chicago Manual of Style (16th Edition):

Ocegueda-Hernandez, Francisco 1978-. “AN EMPIRICAL STUDY OF THE SUITABILITY OF CLASS DECOMPOSITION FOR LINEAR CLASSIFIERS.” 2012. Doctoral Dissertation, University of Houston. Accessed May 08, 2021. http://hdl.handle.net/10657/798.

MLA Handbook (7th Edition):

Ocegueda-Hernandez, Francisco 1978-. “AN EMPIRICAL STUDY OF THE SUITABILITY OF CLASS DECOMPOSITION FOR LINEAR CLASSIFIERS.” 2012. Web. 08 May 2021.

Vancouver:

Ocegueda-Hernandez F1. AN EMPIRICAL STUDY OF THE SUITABILITY OF CLASS DECOMPOSITION FOR LINEAR CLASSIFIERS. [Internet] [Doctoral dissertation]. University of Houston; 2012. [cited 2021 May 08]. Available from: http://hdl.handle.net/10657/798.

Council of Science Editors:

Ocegueda-Hernandez F1. AN EMPIRICAL STUDY OF THE SUITABILITY OF CLASS DECOMPOSITION FOR LINEAR CLASSIFIERS. [Doctoral Dissertation]. University of Houston; 2012. Available from: http://hdl.handle.net/10657/798


George Mason University

27. Naik, Azad. Using Multi-Task Learning For Large-Scale Document Classification .

Degree: 2013, George Mason University

 Multi-Task Learning (MTL) involves learning of multiple tasks, jointly. It seeks to improve the generalization performance of each task by leveraging the relationships among the… (more)

Subjects/Keywords: Multi-Task Learning; classification; model selection; logistic regression; random projection (hashing)

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APA (6th Edition):

Naik, A. (2013). Using Multi-Task Learning For Large-Scale Document Classification . (Thesis). George Mason University. Retrieved from http://hdl.handle.net/1920/8479

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):

Naik, Azad. “Using Multi-Task Learning For Large-Scale Document Classification .” 2013. Thesis, George Mason University. Accessed May 08, 2021. http://hdl.handle.net/1920/8479.

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

MLA Handbook (7th Edition):

Naik, Azad. “Using Multi-Task Learning For Large-Scale Document Classification .” 2013. Web. 08 May 2021.

Vancouver:

Naik A. Using Multi-Task Learning For Large-Scale Document Classification . [Internet] [Thesis]. George Mason University; 2013. [cited 2021 May 08]. Available from: http://hdl.handle.net/1920/8479.

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

Council of Science Editors:

Naik A. Using Multi-Task Learning For Large-Scale Document Classification . [Thesis]. George Mason University; 2013. Available from: http://hdl.handle.net/1920/8479

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

28. FANG YUHANG. MACHINE LEARNING APPROACH FOR FEATURE SELECTION AND CLASSIFICATION OF HIGH-DIMENSIONAL DATA.

Degree: 2019, National University of Singapore

Subjects/Keywords: Machine Learning; Feature Selection; Classification

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APA (6th Edition):

YUHANG, F. (2019). MACHINE LEARNING APPROACH FOR FEATURE SELECTION AND CLASSIFICATION OF HIGH-DIMENSIONAL DATA. (Thesis). National University of Singapore. Retrieved from https://scholarbank.nus.edu.sg/handle/10635/158101

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):

YUHANG, FANG. “MACHINE LEARNING APPROACH FOR FEATURE SELECTION AND CLASSIFICATION OF HIGH-DIMENSIONAL DATA.” 2019. Thesis, National University of Singapore. Accessed May 08, 2021. https://scholarbank.nus.edu.sg/handle/10635/158101.

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

MLA Handbook (7th Edition):

YUHANG, FANG. “MACHINE LEARNING APPROACH FOR FEATURE SELECTION AND CLASSIFICATION OF HIGH-DIMENSIONAL DATA.” 2019. Web. 08 May 2021.

Vancouver:

YUHANG F. MACHINE LEARNING APPROACH FOR FEATURE SELECTION AND CLASSIFICATION OF HIGH-DIMENSIONAL DATA. [Internet] [Thesis]. National University of Singapore; 2019. [cited 2021 May 08]. Available from: https://scholarbank.nus.edu.sg/handle/10635/158101.

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

Council of Science Editors:

YUHANG F. MACHINE LEARNING APPROACH FOR FEATURE SELECTION AND CLASSIFICATION OF HIGH-DIMENSIONAL DATA. [Thesis]. National University of Singapore; 2019. Available from: https://scholarbank.nus.edu.sg/handle/10635/158101

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


Princeton University

29. Wang, Yun. Feature Screening for the Lasso .

Degree: PhD, 2015, Princeton University

 Recently, the sparse representation of data with respect to a dictionary of features has contributed to successful new methods in machine learning, pattern analysis, statistics… (more)

Subjects/Keywords: classification; feature screening; feature selection; lasso; machine learning; sparse representation/regression

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

APA (6th Edition):

Wang, Y. (2015). Feature Screening for the Lasso . (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp01hq37vq979

Chicago Manual of Style (16th Edition):

Wang, Yun. “Feature Screening for the Lasso .” 2015. Doctoral Dissertation, Princeton University. Accessed May 08, 2021. http://arks.princeton.edu/ark:/88435/dsp01hq37vq979.

MLA Handbook (7th Edition):

Wang, Yun. “Feature Screening for the Lasso .” 2015. Web. 08 May 2021.

Vancouver:

Wang Y. Feature Screening for the Lasso . [Internet] [Doctoral dissertation]. Princeton University; 2015. [cited 2021 May 08]. Available from: http://arks.princeton.edu/ark:/88435/dsp01hq37vq979.

Council of Science Editors:

Wang Y. Feature Screening for the Lasso . [Doctoral Dissertation]. Princeton University; 2015. Available from: http://arks.princeton.edu/ark:/88435/dsp01hq37vq979

30. Bellman, Henrietta A. Hurricane and human-induced habitat changes on Fire Island and Westhampton Island, New York, and the effects on breeding piping plovers (Charadrius melodus).

Degree: MS, Fish and Wildlife Conservation, 2019, Virginia Tech

 Barrier islands are thin strips of land, which generally lie parallel to the mainland. They are dynamic environments subject to change from weather conditions and… (more)

Subjects/Keywords: Barrier islands; Charadrius melodus; habitat selection; hurricane; image classification; vegetation succession

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

APA (6th Edition):

Bellman, H. A. (2019). Hurricane and human-induced habitat changes on Fire Island and Westhampton Island, New York, and the effects on breeding piping plovers (Charadrius melodus). (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/87402

Chicago Manual of Style (16th Edition):

Bellman, Henrietta A. “Hurricane and human-induced habitat changes on Fire Island and Westhampton Island, New York, and the effects on breeding piping plovers (Charadrius melodus).” 2019. Masters Thesis, Virginia Tech. Accessed May 08, 2021. http://hdl.handle.net/10919/87402.

MLA Handbook (7th Edition):

Bellman, Henrietta A. “Hurricane and human-induced habitat changes on Fire Island and Westhampton Island, New York, and the effects on breeding piping plovers (Charadrius melodus).” 2019. Web. 08 May 2021.

Vancouver:

Bellman HA. Hurricane and human-induced habitat changes on Fire Island and Westhampton Island, New York, and the effects on breeding piping plovers (Charadrius melodus). [Internet] [Masters thesis]. Virginia Tech; 2019. [cited 2021 May 08]. Available from: http://hdl.handle.net/10919/87402.

Council of Science Editors:

Bellman HA. Hurricane and human-induced habitat changes on Fire Island and Westhampton Island, New York, and the effects on breeding piping plovers (Charadrius melodus). [Masters Thesis]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/87402

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