Trent University Graduate Thesis Collection

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tula:etd
Type
Collection
Language
eng
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1 item
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Copyright for all items in the Trent University Graduate Thesis Collection is held by the author, with all rights reserved, unless otherwise noted.
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Smote and Performance Measures for Machine Learning Applied to Real-Time Bidding

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Year: 2016, 2016
Member of: Trent University Graduate Thesis Collection
Name(s): Creator (cre): McInroy, Ben P., Thesis advisor (ths): Feng, Wenying, Degree committee member (dgc): Patrick, Brian, Degree committee member (dgc): Pollanen, Marco, Degree granting institution (dgg): Trent University
Abstract: <p>In the context of Real-Time Bidding (RTB) the machine learning problems of</p><p>imbalanced classes and model selection are investigated. Synthetic Minority Oversampling Technique (SMOTE) is commonly used to combat imbalanced classes but a shortcoming is identified. Use of a distance threshold is identified as a solution and testing in a live RTB environment shows significant… more
Full Text: SMOTE AND PERFORMANCE MEASURES FOR MACHINE LEARNING APPLIED TO REAL-TIME BIDDING A Thesis Submitted to the Committee of Graduate Studies in Partial Fulfillment of the Requirements for the Degree of Master of Science in the Faculty of Arts and Science …