Multinomial Classification Machine Learning Algorithm Comparison on High-Dimension Leukemia Genomic Data

Tyler Kinkade

The goal of this project was to compare the effectiveness of four multinomial classification machine learning algorithms in distinguishing five types of leukemia based on imbalanced, highly dimensional genomic data in order to better understand the algorithms' strengths and weaknesses within this context. See the Jupyter notebook for the complete report.