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You searched for subject:(Supervised classification). Showing records 1 – 30 of 296 total matches.

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Colorado School of Mines

1. Jackson, Ryan Blake. Machine learning for encrypted Amazon Echo traffic classification.

Degree: MS(M.S.), Computer Science, 2018, Colorado School of Mines

 As smart speakers like the Amazon Echo become more popular, they have given rise to rampant concerns regarding user privacy. This work investigates machine learning… (more)

Subjects/Keywords: supervised classification; machine learning

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APA (6th Edition):

Jackson, R. B. (2018). Machine learning for encrypted Amazon Echo traffic classification. (Masters Thesis). Colorado School of Mines. Retrieved from http://hdl.handle.net/11124/172223

Chicago Manual of Style (16th Edition):

Jackson, Ryan Blake. “Machine learning for encrypted Amazon Echo traffic classification.” 2018. Masters Thesis, Colorado School of Mines. Accessed January 23, 2021. http://hdl.handle.net/11124/172223.

MLA Handbook (7th Edition):

Jackson, Ryan Blake. “Machine learning for encrypted Amazon Echo traffic classification.” 2018. Web. 23 Jan 2021.

Vancouver:

Jackson RB. Machine learning for encrypted Amazon Echo traffic classification. [Internet] [Masters thesis]. Colorado School of Mines; 2018. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/11124/172223.

Council of Science Editors:

Jackson RB. Machine learning for encrypted Amazon Echo traffic classification. [Masters Thesis]. Colorado School of Mines; 2018. Available from: http://hdl.handle.net/11124/172223


McMaster University

2. Ateeq, Sameen. Machine Learning Approach on Evaluating Predictive Factors of Fall-Related Injuries.

Degree: MSc, 2018, McMaster University

According to the Public Health Agency of Canada, falls account for 95% of all hip fractures in Canada; 20% of fall-related injury cases end in… (more)

Subjects/Keywords: machine learning; supervised classification; falls; CCHS; injuries

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APA (6th Edition):

Ateeq, S. (2018). Machine Learning Approach on Evaluating Predictive Factors of Fall-Related Injuries. (Masters Thesis). McMaster University. Retrieved from http://hdl.handle.net/11375/24095

Chicago Manual of Style (16th Edition):

Ateeq, Sameen. “Machine Learning Approach on Evaluating Predictive Factors of Fall-Related Injuries.” 2018. Masters Thesis, McMaster University. Accessed January 23, 2021. http://hdl.handle.net/11375/24095.

MLA Handbook (7th Edition):

Ateeq, Sameen. “Machine Learning Approach on Evaluating Predictive Factors of Fall-Related Injuries.” 2018. Web. 23 Jan 2021.

Vancouver:

Ateeq S. Machine Learning Approach on Evaluating Predictive Factors of Fall-Related Injuries. [Internet] [Masters thesis]. McMaster University; 2018. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/11375/24095.

Council of Science Editors:

Ateeq S. Machine Learning Approach on Evaluating Predictive Factors of Fall-Related Injuries. [Masters Thesis]. McMaster University; 2018. Available from: http://hdl.handle.net/11375/24095


University of Manchester

3. Aguilar Ariza, Andres. MACHINE LEARNING AND BIG DATA TECHNIQUES FOR SATELLITE-BASED RICE PHENOLOGY MONITORING.

Degree: 2019, University of Manchester

 New sources of information are required to support rice production decisions. To cope with this challenge, studies have found practical applications on mapping rice through… (more)

Subjects/Keywords: Remote sensing; Agriculture; Rice phenology; Supervised classification

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APA (6th Edition):

Aguilar Ariza, A. (2019). MACHINE LEARNING AND BIG DATA TECHNIQUES FOR SATELLITE-BASED RICE PHENOLOGY MONITORING. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:320587

Chicago Manual of Style (16th Edition):

Aguilar Ariza, Andres. “MACHINE LEARNING AND BIG DATA TECHNIQUES FOR SATELLITE-BASED RICE PHENOLOGY MONITORING.” 2019. Doctoral Dissertation, University of Manchester. Accessed January 23, 2021. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:320587.

MLA Handbook (7th Edition):

Aguilar Ariza, Andres. “MACHINE LEARNING AND BIG DATA TECHNIQUES FOR SATELLITE-BASED RICE PHENOLOGY MONITORING.” 2019. Web. 23 Jan 2021.

Vancouver:

Aguilar Ariza A. MACHINE LEARNING AND BIG DATA TECHNIQUES FOR SATELLITE-BASED RICE PHENOLOGY MONITORING. [Internet] [Doctoral dissertation]. University of Manchester; 2019. [cited 2021 Jan 23]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:320587.

Council of Science Editors:

Aguilar Ariza A. MACHINE LEARNING AND BIG DATA TECHNIQUES FOR SATELLITE-BASED RICE PHENOLOGY MONITORING. [Doctoral Dissertation]. University of Manchester; 2019. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:320587

4. GOH JIE MEIN. Incorporating linguistically motivated knowledge sources into document classification.

Degree: 2004, National University of Singapore

Subjects/Keywords: supervised document classification

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APA (6th Edition):

MEIN, G. J. (2004). Incorporating linguistically motivated knowledge sources into document classification. (Thesis). National University of Singapore. Retrieved from http://scholarbank.nus.edu.sg/handle/10635/14044

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):

MEIN, GOH JIE. “Incorporating linguistically motivated knowledge sources into document classification.” 2004. Thesis, National University of Singapore. Accessed January 23, 2021. http://scholarbank.nus.edu.sg/handle/10635/14044.

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

MLA Handbook (7th Edition):

MEIN, GOH JIE. “Incorporating linguistically motivated knowledge sources into document classification.” 2004. Web. 23 Jan 2021.

Vancouver:

MEIN GJ. Incorporating linguistically motivated knowledge sources into document classification. [Internet] [Thesis]. National University of Singapore; 2004. [cited 2021 Jan 23]. Available from: http://scholarbank.nus.edu.sg/handle/10635/14044.

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

Council of Science Editors:

MEIN GJ. Incorporating linguistically motivated knowledge sources into document classification. [Thesis]. National University of Singapore; 2004. Available from: http://scholarbank.nus.edu.sg/handle/10635/14044

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


University of Notre Dame

5. Troy William Raeder. Evaluating and Maintaining Classification Algorithms</h1>.

Degree: Computer Science and Engineering, 2012, University of Notre Dame

  Any practical application of machine learning necessarily begins with the selection of a classification algorithm. Generally, practitioners will try several different types of algorithms… (more)

Subjects/Keywords: classification; supervised learning; evaluation; concept drift

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APA (6th Edition):

Raeder, T. W. (2012). Evaluating and Maintaining Classification Algorithms</h1>. (Thesis). University of Notre Dame. Retrieved from https://curate.nd.edu/show/4b29b56616h

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):

Raeder, Troy William. “Evaluating and Maintaining Classification Algorithms</h1>.” 2012. Thesis, University of Notre Dame. Accessed January 23, 2021. https://curate.nd.edu/show/4b29b56616h.

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

MLA Handbook (7th Edition):

Raeder, Troy William. “Evaluating and Maintaining Classification Algorithms</h1>.” 2012. Web. 23 Jan 2021.

Vancouver:

Raeder TW. Evaluating and Maintaining Classification Algorithms</h1>. [Internet] [Thesis]. University of Notre Dame; 2012. [cited 2021 Jan 23]. Available from: https://curate.nd.edu/show/4b29b56616h.

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

Council of Science Editors:

Raeder TW. Evaluating and Maintaining Classification Algorithms</h1>. [Thesis]. University of Notre Dame; 2012. Available from: https://curate.nd.edu/show/4b29b56616h

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


Penn State University

6. Biyani, Prakhar. Analyzing Subjectivity and Sentiment of Online Forums.

Degree: 2014, Penn State University

 Online social media has emerged as a popular medium for seeking and providing information, opinions and social support. Online sites such as discussion forums, blogs… (more)

Subjects/Keywords: Subjectivity analysis; sentiment analysis; classification; supervised learning; semi-supervised learning; online forums

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APA (6th Edition):

Biyani, P. (2014). Analyzing Subjectivity and Sentiment of Online Forums. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/22850

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):

Biyani, Prakhar. “Analyzing Subjectivity and Sentiment of Online Forums.” 2014. Thesis, Penn State University. Accessed January 23, 2021. https://submit-etda.libraries.psu.edu/catalog/22850.

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

MLA Handbook (7th Edition):

Biyani, Prakhar. “Analyzing Subjectivity and Sentiment of Online Forums.” 2014. Web. 23 Jan 2021.

Vancouver:

Biyani P. Analyzing Subjectivity and Sentiment of Online Forums. [Internet] [Thesis]. Penn State University; 2014. [cited 2021 Jan 23]. Available from: https://submit-etda.libraries.psu.edu/catalog/22850.

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

Council of Science Editors:

Biyani P. Analyzing Subjectivity and Sentiment of Online Forums. [Thesis]. Penn State University; 2014. Available from: https://submit-etda.libraries.psu.edu/catalog/22850

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

7. Chzhen, Evgenii. Plug-in methods in classification : Méthodes de type plug-in en classification.

Degree: Docteur es, Mathématiques, 2019, Université Paris-Est

Ce manuscrit étudie plusieurs problèmes de classification sous contraintes. Dans ce cadre de classification, notre objectif est de construire un algorithme qui a des performances… (more)

Subjects/Keywords: Classification contrainte; Classification supervisée; Classification semi-Supervisée; Analyse minimax; Classification par plug-In; Ensembles de confiance; Constrained classification; Supervised classification; Semi-Supervised classification; Minimax analysis; Plug-In classification; Confidence sets

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APA (6th Edition):

Chzhen, E. (2019). Plug-in methods in classification : Méthodes de type plug-in en classification. (Doctoral Dissertation). Université Paris-Est. Retrieved from http://www.theses.fr/2019PESC2027

Chicago Manual of Style (16th Edition):

Chzhen, Evgenii. “Plug-in methods in classification : Méthodes de type plug-in en classification.” 2019. Doctoral Dissertation, Université Paris-Est. Accessed January 23, 2021. http://www.theses.fr/2019PESC2027.

MLA Handbook (7th Edition):

Chzhen, Evgenii. “Plug-in methods in classification : Méthodes de type plug-in en classification.” 2019. Web. 23 Jan 2021.

Vancouver:

Chzhen E. Plug-in methods in classification : Méthodes de type plug-in en classification. [Internet] [Doctoral dissertation]. Université Paris-Est; 2019. [cited 2021 Jan 23]. Available from: http://www.theses.fr/2019PESC2027.

Council of Science Editors:

Chzhen E. Plug-in methods in classification : Méthodes de type plug-in en classification. [Doctoral Dissertation]. Université Paris-Est; 2019. Available from: http://www.theses.fr/2019PESC2027

8. Lehaire, Jérôme. Détection et caractérisation du cancer de la prostate par images IRM 1.5T multiparamétriques : Computer-aided decision system for prostate cancer detection and characterization based on multi-parametric 1.5T MRI.

Degree: Docteur es, Traitement d'images, 2016, Lyon

Le cancer de la prostate est le plus courant en France et la 4ième cause de mortalité par cancer. Les méthodes diagnostics de références actuel… (more)

Subjects/Keywords: IRM 1.5T; CAD; Classification supervisée; IRM 1.5T; CAD; Supervised classification; 616.075

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APA (6th Edition):

Lehaire, J. (2016). Détection et caractérisation du cancer de la prostate par images IRM 1.5T multiparamétriques : Computer-aided decision system for prostate cancer detection and characterization based on multi-parametric 1.5T MRI. (Doctoral Dissertation). Lyon. Retrieved from http://www.theses.fr/2016LYSE1174

Chicago Manual of Style (16th Edition):

Lehaire, Jérôme. “Détection et caractérisation du cancer de la prostate par images IRM 1.5T multiparamétriques : Computer-aided decision system for prostate cancer detection and characterization based on multi-parametric 1.5T MRI.” 2016. Doctoral Dissertation, Lyon. Accessed January 23, 2021. http://www.theses.fr/2016LYSE1174.

MLA Handbook (7th Edition):

Lehaire, Jérôme. “Détection et caractérisation du cancer de la prostate par images IRM 1.5T multiparamétriques : Computer-aided decision system for prostate cancer detection and characterization based on multi-parametric 1.5T MRI.” 2016. Web. 23 Jan 2021.

Vancouver:

Lehaire J. Détection et caractérisation du cancer de la prostate par images IRM 1.5T multiparamétriques : Computer-aided decision system for prostate cancer detection and characterization based on multi-parametric 1.5T MRI. [Internet] [Doctoral dissertation]. Lyon; 2016. [cited 2021 Jan 23]. Available from: http://www.theses.fr/2016LYSE1174.

Council of Science Editors:

Lehaire J. Détection et caractérisation du cancer de la prostate par images IRM 1.5T multiparamétriques : Computer-aided decision system for prostate cancer detection and characterization based on multi-parametric 1.5T MRI. [Doctoral Dissertation]. Lyon; 2016. Available from: http://www.theses.fr/2016LYSE1174

9. Walker, Briana Shanise. Rethinking Document Classification: A Pilot for the Application of Text Mining Techniques To Enhance Standardized Assessment Protocols for Critical Care Medical Team Transfer of Care.

Degree: MSs, Systems Biology and Bioinformatics, 2017, Case Western Reserve University School of Graduate Studies

 The research efforts undertaken in this thesis project represent an extension of the previously published works of Alfes & Reimer (2016). This pilot study evaluates… (more)

Subjects/Keywords: Bioinformatics; Nursing; critical care; transfer of care; text classification; document classification; supervised classification; dialogue

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APA (6th Edition):

Walker, B. S. (2017). Rethinking Document Classification: A Pilot for the Application of Text Mining Techniques To Enhance Standardized Assessment Protocols for Critical Care Medical Team Transfer of Care. (Masters Thesis). Case Western Reserve University School of Graduate Studies. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=case1496760037827537

Chicago Manual of Style (16th Edition):

Walker, Briana Shanise. “Rethinking Document Classification: A Pilot for the Application of Text Mining Techniques To Enhance Standardized Assessment Protocols for Critical Care Medical Team Transfer of Care.” 2017. Masters Thesis, Case Western Reserve University School of Graduate Studies. Accessed January 23, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=case1496760037827537.

MLA Handbook (7th Edition):

Walker, Briana Shanise. “Rethinking Document Classification: A Pilot for the Application of Text Mining Techniques To Enhance Standardized Assessment Protocols for Critical Care Medical Team Transfer of Care.” 2017. Web. 23 Jan 2021.

Vancouver:

Walker BS. Rethinking Document Classification: A Pilot for the Application of Text Mining Techniques To Enhance Standardized Assessment Protocols for Critical Care Medical Team Transfer of Care. [Internet] [Masters thesis]. Case Western Reserve University School of Graduate Studies; 2017. [cited 2021 Jan 23]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1496760037827537.

Council of Science Editors:

Walker BS. Rethinking Document Classification: A Pilot for the Application of Text Mining Techniques To Enhance Standardized Assessment Protocols for Critical Care Medical Team Transfer of Care. [Masters Thesis]. Case Western Reserve University School of Graduate Studies; 2017. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1496760037827537


Rochester Institute of Technology

10. 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 (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 January 23, 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. 23 Jan 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 Jan 23]. 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


Rochester Institute of Technology

11. Karnam, Srivallabha. Self-Supervised Learning for Segmentation using Image Reconstruction.

Degree: MS, Computer Engineering, 2020, Rochester Institute of Technology

  Deep learning is the engine that is piloting tremendous growth in various segments of the industry by consuming valuable fuel called data. We are… (more)

Subjects/Keywords: Classification; Computer vision; Self-supervised learning; Semantic segmentation; Unsupervised learning

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APA (6th Edition):

Karnam, S. (2020). Self-Supervised Learning for Segmentation using Image Reconstruction. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/10532

Chicago Manual of Style (16th Edition):

Karnam, Srivallabha. “Self-Supervised Learning for Segmentation using Image Reconstruction.” 2020. Masters Thesis, Rochester Institute of Technology. Accessed January 23, 2021. https://scholarworks.rit.edu/theses/10532.

MLA Handbook (7th Edition):

Karnam, Srivallabha. “Self-Supervised Learning for Segmentation using Image Reconstruction.” 2020. Web. 23 Jan 2021.

Vancouver:

Karnam S. Self-Supervised Learning for Segmentation using Image Reconstruction. [Internet] [Masters thesis]. Rochester Institute of Technology; 2020. [cited 2021 Jan 23]. Available from: https://scholarworks.rit.edu/theses/10532.

Council of Science Editors:

Karnam S. Self-Supervised Learning for Segmentation using Image Reconstruction. [Masters Thesis]. Rochester Institute of Technology; 2020. Available from: https://scholarworks.rit.edu/theses/10532


University of Tasmania

12. Anees, A. Statistical algorithms for land/forest cover change detection using remote sensing data.

Degree: 2016, University of Tasmania

 Land cover changes significantly affect climate, hydrology, bio-diversity, socio-economic stability and food security. Some of these changes being studied in remote sensing discipline include, but… (more)

Subjects/Keywords: Change detection; remote sensing; statistical algorithms; supervised classification

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APA (6th Edition):

Anees, A. (2016). Statistical algorithms for land/forest cover change detection using remote sensing data. (Thesis). University of Tasmania. Retrieved from https://eprints.utas.edu.au/22984/1/Anees_whole_thesis.pdf

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):

Anees, A. “Statistical algorithms for land/forest cover change detection using remote sensing data.” 2016. Thesis, University of Tasmania. Accessed January 23, 2021. https://eprints.utas.edu.au/22984/1/Anees_whole_thesis.pdf.

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

MLA Handbook (7th Edition):

Anees, A. “Statistical algorithms for land/forest cover change detection using remote sensing data.” 2016. Web. 23 Jan 2021.

Vancouver:

Anees A. Statistical algorithms for land/forest cover change detection using remote sensing data. [Internet] [Thesis]. University of Tasmania; 2016. [cited 2021 Jan 23]. Available from: https://eprints.utas.edu.au/22984/1/Anees_whole_thesis.pdf.

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

Council of Science Editors:

Anees A. Statistical algorithms for land/forest cover change detection using remote sensing data. [Thesis]. University of Tasmania; 2016. Available from: https://eprints.utas.edu.au/22984/1/Anees_whole_thesis.pdf

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


McMaster University

13. Gallaugher, Michael P.B. On Fractionally-Supervised Classification: Weight Selection and Extension to the Multivariate t-Distribution.

Degree: MSc, 2016, McMaster University

Recent work on fractionally-supervised classification (FSC), an approach that allows classification to be carried out with a fractional amount of weight given to the unla-… (more)

Subjects/Keywords: Fractionally Supervised Classification; Clustering; Discriminant Analysis; Mixture Models

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APA (6th Edition):

Gallaugher, M. P. B. (2016). On Fractionally-Supervised Classification: Weight Selection and Extension to the Multivariate t-Distribution. (Masters Thesis). McMaster University. Retrieved from http://hdl.handle.net/11375/20738

Chicago Manual of Style (16th Edition):

Gallaugher, Michael P B. “On Fractionally-Supervised Classification: Weight Selection and Extension to the Multivariate t-Distribution.” 2016. Masters Thesis, McMaster University. Accessed January 23, 2021. http://hdl.handle.net/11375/20738.

MLA Handbook (7th Edition):

Gallaugher, Michael P B. “On Fractionally-Supervised Classification: Weight Selection and Extension to the Multivariate t-Distribution.” 2016. Web. 23 Jan 2021.

Vancouver:

Gallaugher MPB. On Fractionally-Supervised Classification: Weight Selection and Extension to the Multivariate t-Distribution. [Internet] [Masters thesis]. McMaster University; 2016. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/11375/20738.

Council of Science Editors:

Gallaugher MPB. On Fractionally-Supervised Classification: Weight Selection and Extension to the Multivariate t-Distribution. [Masters Thesis]. McMaster University; 2016. Available from: http://hdl.handle.net/11375/20738


Tampere University

14. Hussain, Yasir. Predicting customer satisfaction with product reviews: A comparitive study of some machine learning approaches.

Degree: 2019, Tampere University

 In past two decades e-commerce platform developed exponentially, and with this advent, there came several challenges due to a vast amount of information. Customers not… (more)

Subjects/Keywords: Supervised Machine Learning; NLP; Amazon Reviews; Customer Satisfaction; Classification

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APA (6th Edition):

Hussain, Y. (2019). Predicting customer satisfaction with product reviews: A comparitive study of some machine learning approaches. (Masters Thesis). Tampere University. Retrieved from https://trepo.tuni.fi/handle/10024/118686

Chicago Manual of Style (16th Edition):

Hussain, Yasir. “Predicting customer satisfaction with product reviews: A comparitive study of some machine learning approaches. ” 2019. Masters Thesis, Tampere University. Accessed January 23, 2021. https://trepo.tuni.fi/handle/10024/118686.

MLA Handbook (7th Edition):

Hussain, Yasir. “Predicting customer satisfaction with product reviews: A comparitive study of some machine learning approaches. ” 2019. Web. 23 Jan 2021.

Vancouver:

Hussain Y. Predicting customer satisfaction with product reviews: A comparitive study of some machine learning approaches. [Internet] [Masters thesis]. Tampere University; 2019. [cited 2021 Jan 23]. Available from: https://trepo.tuni.fi/handle/10024/118686.

Council of Science Editors:

Hussain Y. Predicting customer satisfaction with product reviews: A comparitive study of some machine learning approaches. [Masters Thesis]. Tampere University; 2019. Available from: https://trepo.tuni.fi/handle/10024/118686


Universidade Nova

15. Last, Felix. Oversampling for imbalanced learning based on k-means and smote.

Degree: 2018, Universidade Nova

 Learning from class-imbalanced data continues to be a common and challenging problem in supervised learning as standard classification algorithms are designed to handle balanced class… (more)

Subjects/Keywords: Class-imbalanced learning; Oversampling; Classification; Clustering; Supervised learning

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APA (6th Edition):

Last, F. (2018). Oversampling for imbalanced learning based on k-means and smote. (Thesis). Universidade Nova. Retrieved from https://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/31042

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):

Last, Felix. “Oversampling for imbalanced learning based on k-means and smote.” 2018. Thesis, Universidade Nova. Accessed January 23, 2021. https://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/31042.

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

MLA Handbook (7th Edition):

Last, Felix. “Oversampling for imbalanced learning based on k-means and smote.” 2018. Web. 23 Jan 2021.

Vancouver:

Last F. Oversampling for imbalanced learning based on k-means and smote. [Internet] [Thesis]. Universidade Nova; 2018. [cited 2021 Jan 23]. Available from: https://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/31042.

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

Council of Science Editors:

Last F. Oversampling for imbalanced learning based on k-means and smote. [Thesis]. Universidade Nova; 2018. Available from: https://www.rcaap.pt/detail.jsp?id=oai:run.unl.pt:10362/31042

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


University of Illinois – Chicago

16. Randazzo, Ettore. Inferring Interaction Network from Sensor Data.

Degree: 2016, University of Illinois – Chicago

 Being able to observe how animals interact among themselves has always been a crucial requirement for behavioral scientists who study social species. Physically watching them… (more)

Subjects/Keywords: animal behaviour; supervised learning; inference; classification; machine learning; dyadic interactions

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

APA (6th Edition):

Randazzo, E. (2016). Inferring Interaction Network from Sensor Data. (Thesis). University of Illinois – Chicago. Retrieved from http://hdl.handle.net/10027/21233

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):

Randazzo, Ettore. “Inferring Interaction Network from Sensor Data.” 2016. Thesis, University of Illinois – Chicago. Accessed January 23, 2021. http://hdl.handle.net/10027/21233.

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

MLA Handbook (7th Edition):

Randazzo, Ettore. “Inferring Interaction Network from Sensor Data.” 2016. Web. 23 Jan 2021.

Vancouver:

Randazzo E. Inferring Interaction Network from Sensor Data. [Internet] [Thesis]. University of Illinois – Chicago; 2016. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10027/21233.

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

Council of Science Editors:

Randazzo E. Inferring Interaction Network from Sensor Data. [Thesis]. University of Illinois – Chicago; 2016. Available from: http://hdl.handle.net/10027/21233

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


KTH

17. Lundberg, Ludvig. Damage Assessment of Mozambique Flooding Using Sentinel.

Degree: Geoinformatics, 2020, KTH

  In the past 40 years, floods have become a bane of Mozambique’s inhabitants and economy. The latest of them, caused by the cyclone Idai,… (more)

Subjects/Keywords: change detection; supervised classification; sentinel; Mozambique; Other Social Sciences; Annan samhällsvetenskap

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

APA (6th Edition):

Lundberg, L. (2020). Damage Assessment of Mozambique Flooding Using Sentinel. (Thesis). KTH. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-272396

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):

Lundberg, Ludvig. “Damage Assessment of Mozambique Flooding Using Sentinel.” 2020. Thesis, KTH. Accessed January 23, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-272396.

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

MLA Handbook (7th Edition):

Lundberg, Ludvig. “Damage Assessment of Mozambique Flooding Using Sentinel.” 2020. Web. 23 Jan 2021.

Vancouver:

Lundberg L. Damage Assessment of Mozambique Flooding Using Sentinel. [Internet] [Thesis]. KTH; 2020. [cited 2021 Jan 23]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-272396.

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

Council of Science Editors:

Lundberg L. Damage Assessment of Mozambique Flooding Using Sentinel. [Thesis]. KTH; 2020. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-272396

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


University of Miami

18. Quirino, Thiago S. Improving Search In Genetic Algorithms Through Instinct-Based Mating Strategies.

Degree: PhD, Electrical and Computer Engineering (Engineering), 2012, University of Miami

 The Genetic Algorithm (GA) is a popular approach to search and optimization that has been applied to hundreds of real-world optimization problems across numerous domains… (more)

Subjects/Keywords: Genetic Algorithms; Mating Strategies; Machine Learning; Optimization; Data Mining; Supervised Classification

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

APA (6th Edition):

Quirino, T. S. (2012). Improving Search In Genetic Algorithms Through Instinct-Based Mating Strategies. (Doctoral Dissertation). University of Miami. Retrieved from https://scholarlyrepository.miami.edu/oa_dissertations/737

Chicago Manual of Style (16th Edition):

Quirino, Thiago S. “Improving Search In Genetic Algorithms Through Instinct-Based Mating Strategies.” 2012. Doctoral Dissertation, University of Miami. Accessed January 23, 2021. https://scholarlyrepository.miami.edu/oa_dissertations/737.

MLA Handbook (7th Edition):

Quirino, Thiago S. “Improving Search In Genetic Algorithms Through Instinct-Based Mating Strategies.” 2012. Web. 23 Jan 2021.

Vancouver:

Quirino TS. Improving Search In Genetic Algorithms Through Instinct-Based Mating Strategies. [Internet] [Doctoral dissertation]. University of Miami; 2012. [cited 2021 Jan 23]. Available from: https://scholarlyrepository.miami.edu/oa_dissertations/737.

Council of Science Editors:

Quirino TS. Improving Search In Genetic Algorithms Through Instinct-Based Mating Strategies. [Doctoral Dissertation]. University of Miami; 2012. Available from: https://scholarlyrepository.miami.edu/oa_dissertations/737


University of Houston

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

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

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

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

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

APA (6th Edition):

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

Chicago Manual of Style (16th Edition):

Amalaman, Paul K 1966-. “New Approaches to Hierarchical Modeling — Frameworks, Algorithms, and Applications.” 2015. Doctoral Dissertation, University of Houston. Accessed January 23, 2021. http://hdl.handle.net/10657/4888.

MLA Handbook (7th Edition):

Amalaman, Paul K 1966-. “New Approaches to Hierarchical Modeling — Frameworks, Algorithms, and Applications.” 2015. Web. 23 Jan 2021.

Vancouver:

Amalaman PK1. New Approaches to Hierarchical Modeling — Frameworks, Algorithms, and Applications. [Internet] [Doctoral dissertation]. University of Houston; 2015. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/10657/4888.

Council of Science Editors:

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


University of Connecticut

20. zhao, xiaojun. Machine Learning Approaches to 3D Model Classification.

Degree: MS, Mechanical Engineering, 2015, University of Connecticut

  A desirable 3D model classification system should be equipped with qualities such as highly correct classification accuracy, good enough classification speed, robustness to model… (more)

Subjects/Keywords: 3D model; Classification; Machine learning; Shape Descriptors; Supervised Learning

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

APA (6th Edition):

zhao, x. (2015). Machine Learning Approaches to 3D Model Classification. (Masters Thesis). University of Connecticut. Retrieved from https://opencommons.uconn.edu/gs_theses/820

Chicago Manual of Style (16th Edition):

zhao, xiaojun. “Machine Learning Approaches to 3D Model Classification.” 2015. Masters Thesis, University of Connecticut. Accessed January 23, 2021. https://opencommons.uconn.edu/gs_theses/820.

MLA Handbook (7th Edition):

zhao, xiaojun. “Machine Learning Approaches to 3D Model Classification.” 2015. Web. 23 Jan 2021.

Vancouver:

zhao x. Machine Learning Approaches to 3D Model Classification. [Internet] [Masters thesis]. University of Connecticut; 2015. [cited 2021 Jan 23]. Available from: https://opencommons.uconn.edu/gs_theses/820.

Council of Science Editors:

zhao x. Machine Learning Approaches to 3D Model Classification. [Masters Thesis]. University of Connecticut; 2015. Available from: https://opencommons.uconn.edu/gs_theses/820


Université Catholique de Louvain

21. Amouh, Teh. Analysis of tabular non-standard data with decision trees, and application to hypnogram-based detection of sleep profile.

Degree: 2011, Université Catholique de Louvain

 The amount of data in the world and in our lives seems ever-increasing and there is no end in sight. Such a situation is supported… (more)

Subjects/Keywords: Supervised classification; Clustering; Decision trees; Non-standard data; Sleep analysis

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

APA (6th Edition):

Amouh, T. (2011). Analysis of tabular non-standard data with decision trees, and application to hypnogram-based detection of sleep profile. (Thesis). Université Catholique de Louvain. Retrieved from http://hdl.handle.net/2078.1/105005

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):

Amouh, Teh. “Analysis of tabular non-standard data with decision trees, and application to hypnogram-based detection of sleep profile.” 2011. Thesis, Université Catholique de Louvain. Accessed January 23, 2021. http://hdl.handle.net/2078.1/105005.

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

MLA Handbook (7th Edition):

Amouh, Teh. “Analysis of tabular non-standard data with decision trees, and application to hypnogram-based detection of sleep profile.” 2011. Web. 23 Jan 2021.

Vancouver:

Amouh T. Analysis of tabular non-standard data with decision trees, and application to hypnogram-based detection of sleep profile. [Internet] [Thesis]. Université Catholique de Louvain; 2011. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/2078.1/105005.

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

Council of Science Editors:

Amouh T. Analysis of tabular non-standard data with decision trees, and application to hypnogram-based detection of sleep profile. [Thesis]. Université Catholique de Louvain; 2011. Available from: http://hdl.handle.net/2078.1/105005

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

22. Webb, Dean. Efficient piecewise linear classifiers and applications.

Degree: PhD, 2011, Federation University Australia

Supervised learning has become an essential part of data mining for industry, military, science and academia. Classification, a type of supervised learning allows a machine… (more)

Subjects/Keywords: Data mining; Data classification; Supervised learning; Artificial intelligence; Knowledge-based systems

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

APA (6th Edition):

Webb, D. (2011). Efficient piecewise linear classifiers and applications. (Doctoral Dissertation). Federation University Australia. Retrieved from http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/61668

Chicago Manual of Style (16th Edition):

Webb, Dean. “Efficient piecewise linear classifiers and applications.” 2011. Doctoral Dissertation, Federation University Australia. Accessed January 23, 2021. http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/61668.

MLA Handbook (7th Edition):

Webb, Dean. “Efficient piecewise linear classifiers and applications.” 2011. Web. 23 Jan 2021.

Vancouver:

Webb D. Efficient piecewise linear classifiers and applications. [Internet] [Doctoral dissertation]. Federation University Australia; 2011. [cited 2021 Jan 23]. Available from: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/61668.

Council of Science Editors:

Webb D. Efficient piecewise linear classifiers and applications. [Doctoral Dissertation]. Federation University Australia; 2011. Available from: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/61668


Karlstad University

23. Westlinder, Simon. Video Traffic Classification : A Machine Learning approach with Packet Based Features using Support Vector Machine.

Degree: Mathematics and Computer Science (from 2013), 2016, Karlstad University

Internet traffic classification is an important field which several stakeholders are dependent on for a number of different reasons. Internet Service Providers (ISPs) and… (more)

Subjects/Keywords: Supervised Machine Learning; SVM; Video traffic classification; Computer Sciences; Datavetenskap (datalogi)

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

APA (6th Edition):

Westlinder, S. (2016). Video Traffic Classification : A Machine Learning approach with Packet Based Features using Support Vector Machine. (Thesis). Karlstad University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-43011

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):

Westlinder, Simon. “Video Traffic Classification : A Machine Learning approach with Packet Based Features using Support Vector Machine.” 2016. Thesis, Karlstad University. Accessed January 23, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-43011.

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

MLA Handbook (7th Edition):

Westlinder, Simon. “Video Traffic Classification : A Machine Learning approach with Packet Based Features using Support Vector Machine.” 2016. Web. 23 Jan 2021.

Vancouver:

Westlinder S. Video Traffic Classification : A Machine Learning approach with Packet Based Features using Support Vector Machine. [Internet] [Thesis]. Karlstad University; 2016. [cited 2021 Jan 23]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-43011.

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

Council of Science Editors:

Westlinder S. Video Traffic Classification : A Machine Learning approach with Packet Based Features using Support Vector Machine. [Thesis]. Karlstad University; 2016. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-43011

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


Delft University of Technology

24. Smalbil, Jos (author). Web-Based Economic Activity Classification: Comparing semi-supervised text classification methods to deal with noisy labels.

Degree: 2020, Delft University of Technology

In order to provide accurate statistics for industries, the classification of enterprises by economic activity is an important task for national statistical institutes. The economic… (more)

Subjects/Keywords: text mining; label noise; text classification; semi-supervised learning

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

APA (6th Edition):

Smalbil, J. (. (2020). Web-Based Economic Activity Classification: Comparing semi-supervised text classification methods to deal with noisy labels. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:f5f96ef9-8665-4c93-a932-34b8441976b0

Chicago Manual of Style (16th Edition):

Smalbil, Jos (author). “Web-Based Economic Activity Classification: Comparing semi-supervised text classification methods to deal with noisy labels.” 2020. Masters Thesis, Delft University of Technology. Accessed January 23, 2021. http://resolver.tudelft.nl/uuid:f5f96ef9-8665-4c93-a932-34b8441976b0.

MLA Handbook (7th Edition):

Smalbil, Jos (author). “Web-Based Economic Activity Classification: Comparing semi-supervised text classification methods to deal with noisy labels.” 2020. Web. 23 Jan 2021.

Vancouver:

Smalbil J(. Web-Based Economic Activity Classification: Comparing semi-supervised text classification methods to deal with noisy labels. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2021 Jan 23]. Available from: http://resolver.tudelft.nl/uuid:f5f96ef9-8665-4c93-a932-34b8441976b0.

Council of Science Editors:

Smalbil J(. Web-Based Economic Activity Classification: Comparing semi-supervised text classification methods to deal with noisy labels. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:f5f96ef9-8665-4c93-a932-34b8441976b0


University of Minnesota

25. Valovage, Mark. Enhancing Machine Learning Classification for Electrical Time Series with Additional Domain Applications.

Degree: PhD, Computer Science, 2019, University of Minnesota

 Recent advances in machine learning have significant, far-reaching potential in electrical time series applications. However, many methods cannot currently be implemented in real world applications… (more)

Subjects/Keywords: Classification; Electricity Disaggregation; Shapelets; Supervised Learning; Time Series; Unsupervised Learning

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

APA (6th Edition):

Valovage, M. (2019). Enhancing Machine Learning Classification for Electrical Time Series with Additional Domain Applications. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/211812

Chicago Manual of Style (16th Edition):

Valovage, Mark. “Enhancing Machine Learning Classification for Electrical Time Series with Additional Domain Applications.” 2019. Doctoral Dissertation, University of Minnesota. Accessed January 23, 2021. http://hdl.handle.net/11299/211812.

MLA Handbook (7th Edition):

Valovage, Mark. “Enhancing Machine Learning Classification for Electrical Time Series with Additional Domain Applications.” 2019. Web. 23 Jan 2021.

Vancouver:

Valovage M. Enhancing Machine Learning Classification for Electrical Time Series with Additional Domain Applications. [Internet] [Doctoral dissertation]. University of Minnesota; 2019. [cited 2021 Jan 23]. Available from: http://hdl.handle.net/11299/211812.

Council of Science Editors:

Valovage M. Enhancing Machine Learning Classification for Electrical Time Series with Additional Domain Applications. [Doctoral Dissertation]. University of Minnesota; 2019. Available from: http://hdl.handle.net/11299/211812


Georgia State University

26. Wang, Xiaoyuan. Data Mining Analysis of the Parkinson's Disease.

Degree: MS, Mathematics and Statistics, 2014, Georgia State University

  Biological research is becoming increasingly database driven and statistical learning can be used to discover patterns in the biological data. In the thesis, the… (more)

Subjects/Keywords: Supervised Learning; Cross Validation; Prediction Analysis; Classification; Model Selection; ROC Curve

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

APA (6th Edition):

Wang, X. (2014). Data Mining Analysis of the Parkinson's Disease. (Thesis). Georgia State University. Retrieved from https://scholarworks.gsu.edu/math_theses/143

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):

Wang, Xiaoyuan. “Data Mining Analysis of the Parkinson's Disease.” 2014. Thesis, Georgia State University. Accessed January 23, 2021. https://scholarworks.gsu.edu/math_theses/143.

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

MLA Handbook (7th Edition):

Wang, Xiaoyuan. “Data Mining Analysis of the Parkinson's Disease.” 2014. Web. 23 Jan 2021.

Vancouver:

Wang X. Data Mining Analysis of the Parkinson's Disease. [Internet] [Thesis]. Georgia State University; 2014. [cited 2021 Jan 23]. Available from: https://scholarworks.gsu.edu/math_theses/143.

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

Council of Science Editors:

Wang X. Data Mining Analysis of the Parkinson's Disease. [Thesis]. Georgia State University; 2014. Available from: https://scholarworks.gsu.edu/math_theses/143

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


Delft University of Technology

27. Rietveld, T.M. (author). The Effect of Temporal Supervision on the Prediction of Self-reported Emotion from Behavioural Features.

Degree: 2020, Delft University of Technology

 Continuous affective self-reports are intrusive and expensive to acquire, forcing researchers to use alternative labels for the construction of their predictive models. The most predominantly… (more)

Subjects/Keywords: Affective Computing; Emotion Classification; Self-reports; Machine Learning; Weakly Supervised Learning

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

APA (6th Edition):

Rietveld, T. M. (. (2020). The Effect of Temporal Supervision on the Prediction of Self-reported Emotion from Behavioural Features. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:d9ecc6f2-19ab-4dc4-b3b4-513c7285677d

Chicago Manual of Style (16th Edition):

Rietveld, T M (author). “The Effect of Temporal Supervision on the Prediction of Self-reported Emotion from Behavioural Features.” 2020. Masters Thesis, Delft University of Technology. Accessed January 23, 2021. http://resolver.tudelft.nl/uuid:d9ecc6f2-19ab-4dc4-b3b4-513c7285677d.

MLA Handbook (7th Edition):

Rietveld, T M (author). “The Effect of Temporal Supervision on the Prediction of Self-reported Emotion from Behavioural Features.” 2020. Web. 23 Jan 2021.

Vancouver:

Rietveld TM(. The Effect of Temporal Supervision on the Prediction of Self-reported Emotion from Behavioural Features. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2021 Jan 23]. Available from: http://resolver.tudelft.nl/uuid:d9ecc6f2-19ab-4dc4-b3b4-513c7285677d.

Council of Science Editors:

Rietveld TM(. The Effect of Temporal Supervision on the Prediction of Self-reported Emotion from Behavioural Features. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:d9ecc6f2-19ab-4dc4-b3b4-513c7285677d


Carnegie Mellon University

28. Zhang, Yi. Learning with Limited Supervision by Input and Output Coding.

Degree: 2012, Carnegie Mellon University

 In many real-world applications of supervised learning, only a limited number of labeled examples are available because the cost of obtaining high-quality examples is high.… (more)

Subjects/Keywords: regularization; error-correcting output codes; supervised learning; semi-supervised learning; multi-task learning; multi-label classification; dimensionality reduction; Computer Sciences

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

APA (6th Edition):

Zhang, Y. (2012). Learning with Limited Supervision by Input and Output Coding. (Thesis). Carnegie Mellon University. Retrieved from http://repository.cmu.edu/dissertations/156

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):

Zhang, Yi. “Learning with Limited Supervision by Input and Output Coding.” 2012. Thesis, Carnegie Mellon University. Accessed January 23, 2021. http://repository.cmu.edu/dissertations/156.

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

MLA Handbook (7th Edition):

Zhang, Yi. “Learning with Limited Supervision by Input and Output Coding.” 2012. Web. 23 Jan 2021.

Vancouver:

Zhang Y. Learning with Limited Supervision by Input and Output Coding. [Internet] [Thesis]. Carnegie Mellon University; 2012. [cited 2021 Jan 23]. Available from: http://repository.cmu.edu/dissertations/156.

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

Council of Science Editors:

Zhang Y. Learning with Limited Supervision by Input and Output Coding. [Thesis]. Carnegie Mellon University; 2012. Available from: http://repository.cmu.edu/dissertations/156

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

29. Gutiérrez, Victor Antonio Laguna. Classificação semi-supervisionada baseada em desacordo por similaridade.

Degree: Mestrado, Ciências de Computação e Matemática Computacional, 2010, University of São Paulo

O aprendizado semi-supervisionado é um paradigma do aprendizado de máquina no qual a hipótese é induzida aproveitando tanto os dados rotulados quantos os dados não… (more)

Subjects/Keywords: Aprendizado baseado em desacordo; Aprendizado semi-supervisionado; Classificação; Classification; Contraining; Cotraining; Semi-supervised leaning; Semi-supervised learning based in disagreement

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

APA (6th Edition):

Gutiérrez, V. A. L. (2010). Classificação semi-supervisionada baseada em desacordo por similaridade. (Masters Thesis). University of São Paulo. Retrieved from http://www.teses.usp.br/teses/disponiveis/55/55134/tde-21062010-142145/ ;

Chicago Manual of Style (16th Edition):

Gutiérrez, Victor Antonio Laguna. “Classificação semi-supervisionada baseada em desacordo por similaridade.” 2010. Masters Thesis, University of São Paulo. Accessed January 23, 2021. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-21062010-142145/ ;.

MLA Handbook (7th Edition):

Gutiérrez, Victor Antonio Laguna. “Classificação semi-supervisionada baseada em desacordo por similaridade.” 2010. Web. 23 Jan 2021.

Vancouver:

Gutiérrez VAL. Classificação semi-supervisionada baseada em desacordo por similaridade. [Internet] [Masters thesis]. University of São Paulo; 2010. [cited 2021 Jan 23]. Available from: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-21062010-142145/ ;.

Council of Science Editors:

Gutiérrez VAL. Classificação semi-supervisionada baseada em desacordo por similaridade. [Masters Thesis]. University of São Paulo; 2010. Available from: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-21062010-142145/ ;

30. Znaidia, Amel. Handling imperfections for multimodal image annotation : Gestion des imperfections pour l’annotation multimodale d’images.

Degree: Docteur es, Computer science, 2014, Châtenay-Malabry, Ecole centrale de Paris

La présente thèse s’intéresse à l’annotation multimodale d’images dans le contexte des médias sociaux. Notre objectif est de combiner les modalités visuelles et textuelles (tags)… (more)

Subjects/Keywords: Annotation multimodale d’images; Classification supervisée d’images; Imperfections; Multimodal image annotation; Supervised image classification; Tag imperfections

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APA (6th Edition):

Znaidia, A. (2014). Handling imperfections for multimodal image annotation : Gestion des imperfections pour l’annotation multimodale d’images. (Doctoral Dissertation). Châtenay-Malabry, Ecole centrale de Paris. Retrieved from http://www.theses.fr/2014ECAP0017

Chicago Manual of Style (16th Edition):

Znaidia, Amel. “Handling imperfections for multimodal image annotation : Gestion des imperfections pour l’annotation multimodale d’images.” 2014. Doctoral Dissertation, Châtenay-Malabry, Ecole centrale de Paris. Accessed January 23, 2021. http://www.theses.fr/2014ECAP0017.

MLA Handbook (7th Edition):

Znaidia, Amel. “Handling imperfections for multimodal image annotation : Gestion des imperfections pour l’annotation multimodale d’images.” 2014. Web. 23 Jan 2021.

Vancouver:

Znaidia A. Handling imperfections for multimodal image annotation : Gestion des imperfections pour l’annotation multimodale d’images. [Internet] [Doctoral dissertation]. Châtenay-Malabry, Ecole centrale de Paris; 2014. [cited 2021 Jan 23]. Available from: http://www.theses.fr/2014ECAP0017.

Council of Science Editors:

Znaidia A. Handling imperfections for multimodal image annotation : Gestion des imperfections pour l’annotation multimodale d’images. [Doctoral Dissertation]. Châtenay-Malabry, Ecole centrale de Paris; 2014. Available from: http://www.theses.fr/2014ECAP0017

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