1. Objective 1: Use Weka’s WrapperSubsetEval (Naïve Bayes
classifier) and Genetic Search for optimal attribute selection
on breast-cancer diagnostic data. Compare performance
with the optimal subset of attributes to that with the full set.
Objective 2: Classify the leukemia gene expression
data with several sets of 5 genes using IBk (K=5) as in
assignment 1. Record performance by, at least, percent
correct classifications and confusion matrix.
Objective 3: Using “InfoGainAttributeEval” and “Ranker” find
the top 5 genes ranked by information gain. Compare the
performance of IBk (K=5) with these genes to your results
with 5 randomly chosen genes.