Microarray-Data-Analysis

Comparative analysis of feature selection technique with various classification algorithms on a microarray dataset. In this project, we have analysed a microarray dataset using various machine learning algorithms. We have performed feature selection techniques and then applied various classifier models for prediction of leukemia disease. The training(38 samples) and testing(34 samples) datasets were used in the paper contain measurements corresponding to ALL and AML samples from Bone Marrow and Peripheral Blood. This work focuses on a comparative study of the state-of-the-art feature selection and classification algorithms.