Improving classification accuracy of cancer types using parallel hybrid feature selection on microarray gene expression data.

Background: Data mining techniques are used to mine unknown knowledge from huge data. Microarray gene expression (MGE) data plays a major role in predicting type of cancer. But as MGE data is huge in volume, applying traditional data mining approaches is time consuming.