Evaluation of a machine learning tool in the domain of genetic host responses

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pitt_report.pdf (1.48 MB)
Type of content
Reports
UC permalink
http://hdl.handle.net/10092/10181
Publisher's DOI/URI
Thesis discipline
Degree name
Bachelor of Science with Honours
Publisher
University of Canterbury. Computer Science
Journal Title
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Volume Title
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Date
2003
Authors
Pitt, Joel
Abstract

This report examines the use of Support Vector Machines and Genetic Programming Classifiers (GPCs) to distinguish between classes of cancer based on gene expression data. The effect of feature selection on classifier accuracy and on the convergence time of GPCs is experimentally investigated, with the goal of making classification problems on gene expression data tractable to GPCs.

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Keywords
Ngā upoko tukutuku/Māori subject headings
ANZSRC fields of research
Fields of Research::46 - Information and computing sciences::4601 - Applied computing::460103 - Applications in life sciences
Field of Research::06 - Biological Sciences::0604 - Genetics
Rights
Copyright Joel Pitt
https://canterbury.libguides.com/rights/theses
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Engineering: Reports