Machine learning evaluations using WEKA : Honors Thesis, Spring 2020
- ECSU Author/Contributor (non-ECSU co-authors, if there are any, appear on document)
- Thomas Johnson, Student (Creator)
- Institution
- Elizabeth City State University (ECSU )
- Web Site: https://www.ecsu.edu/academics/library/index.html
- Advisor
- Andre P. Stevenson
Abstract: Computer science is a growing field and machine learning is a growing area withincomputer science. The development of various machine learning algorithms that have beencreated has been diverse. Using WEKA, the study used the mammography dataset to examinemachine learning algorithms to explain what components of the machine learning algorithmsmay affect performance. The logistic regression model classified the most instances of theprovided partitioned mammogram dataset. Results indicated an expansion in the assortment ofmachine learning algorithms would be employed generating a larger collection of models.
Machine learning evaluations using WEKA : Honors Thesis, Spring 2020
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Created on 12/1/2020
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Additional Information
- Publication
- Dissertation
- Language: English
- Date: 2020
- Keywords
- machine learning, algorithms, WEKA, logistic regression
- Subjects
- Artificial intelligence
- Machine theory
- Computational learning theory