In this project, we reduced an imbalanced dataset (Undersampling) by Consensus Clustering using 'Simple Majority Voting' consensus function and further saw the increase in the accuracy of disease prediction by running multiple classifers with bagging and boosting technique.

The dataset we have is the colon cancer dataset of (62x2000) dimension.

This is the final result, i.e. comparison of different classifiers of predicting the disease accurately in both balanced and imbalanced data.