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)
Andre P. Stevenson, Professor of Social Work (Contributor)
Institution
Elizabeth City State University (ECSU )
Web Site: https://www.ecsu.edu/academics/library/index.html

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.

Additional Information

Publication
Dissertation
Language: English
Date: 2020
Keywords
machine learning, algorithms, WEKA, logistic regression
Subjects
Artificial intelligence
Machine theory
Computational learning theory

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