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MATHUR_Tanmay_Thesis_12182014.pdf (1.43 MB)

ETD Abstract Container

Abstract Header

Improving Classification Results Using Class Imbalance Solutions & Evaluating the Generalizability of Rationale Extraction Techniques

Mathur, Tanmay
http://rave.ohiolink.edu/etdc/view?acc_num=miami1420335486

Abstract Details

2015, Master of Computer Science, Miami University, Computer Science and Software Engineering.
During the software development process many decisions are made. The decisions, alternatives, and the reasons for and against those alternatives constitute the software design rationale. The research tries to improve the rationale classification results by use of new features. An improvement was observed only for rationale classification but other rationale types showed a F measure reduction. The research also evaluates the generalizability of the machine learning approach using a new dataset though does not establish it. The research implements and experiments with SMOTEBoost algorithm that is used in combination with the new features to give improved results for some categories of rationale. The thesis also describes a tool that can map classified outputs to the original instances that can be used to find missing features.
Janet Burge (Advisor)
Michael Zmuda (Committee Member)
James Kiper (Committee Member)
56 p.
Computer Science
rationale extraction; Chrome Bug Reports; SPSD

Recommended Citations

Citations

  • Mathur, T. (2015). Improving Classification Results Using Class Imbalance Solutions & Evaluating the Generalizability of Rationale Extraction Techniques [Master's thesis, Miami University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=miami1420335486

    APA Style (7th edition)

  • Mathur, Tanmay. Improving Classification Results Using Class Imbalance Solutions & Evaluating the Generalizability of Rationale Extraction Techniques. 2015. Miami University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=miami1420335486.

    MLA Style (8th edition)

  • Mathur, Tanmay. "Improving Classification Results Using Class Imbalance Solutions & Evaluating the Generalizability of Rationale Extraction Techniques." Master's thesis, Miami University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=miami1420335486

    Chicago Manual of Style (17th edition)

miami1420335486
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This open access ETD is published by Miami University and OhioLINK.