New Feature Selection Process to Enhance Naïve Bayes Classification project concentrates on improving the classification accuracy of cancer cells using gene microarray as features for various cancer data sets such as colon cancer, lymphoma and leukemia, using Machine learning classifiers such as Naïve Bayes, along with Point wise mutual information (PMIGS) as feature selection technique. obtained efficient Model accuracy of 98.66%
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New Feature Selection Process to Enhance Naïve Bayes Classification project concentrates on improving the classification accuracy of cancer cells using gene microarray as features for various cancer data sets using Machine learning classifiers , along with point wise mutual information (PMIGS) as feature selection technique.
ash-sha/Enhanced-Feature-Selection-Classification
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New Feature Selection Process to Enhance Naïve Bayes Classification project concentrates on improving the classification accuracy of cancer cells using gene microarray as features for various cancer data sets using Machine learning classifiers , along with point wise mutual information (PMIGS) as feature selection technique.