In many situations costly tests lead to a final diagnosis. Based on past data, it is a hard problem to find the best diagnosis based on the attributes. Even harder to find the one which provides the best diagnosis at the smallest expected cost. In this project, we evaluate and extend a dynamic programming algorithm solving this problem.
Week 1: Met mentor, realized he was going to be out of town for 5 weeks, sought new mentor
McKinney et al. "Machine Learning for Detecting Gene-Gene Interactions"
Guyon, Weston, and Barnhill. "Gene Selection for Cancer Classification using Support Vector Machines"
Gunn, Steve. "Support Vector Machines for Classification and Regression"