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 mutual information as feature selection technique. This 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 mutual information as feature selection technique. obtained efficient Model accuracy of 98.66%
Datasets: Microarray Gene Datasets of Colon, Leukaemia & Lymphoma cancer of 7000+ gene expressions