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Acute Leukemia Classification Using Bayesian Networks

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Executive Summary

In this paper, two models for constructing acute leukemia classifiers using the Signal-to-Noise Ratio (SNR) gene selection method in conjunction with the Bayesian Networks (BNs) have been proposed. In the first model, genes of the acute leukemia training dataset are ranked using the SNR method and then top ranked genes are selected and used to construct the acute leukemia BN classifier. In the second model, genes of the acute leukemia training dataset are clustered using the k-means clustering and then genes of each cluster are ranked using the SNR method after that top ranked genes from gene clusters are selected and used to construct the acute leukemia BN classifier.

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