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Objective 1 : Use Weka’s WrapperSubsetEval (Naïve Bayes

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

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Objective 1 : Use Weka’s WrapperSubsetEval (Naïve Bayes

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  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.

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