Before revision:  In this paper, we theoretically analyze when and how clustering may help in obtaining accurate classifiers. We design a simple , efficient, and generic framework called Classification Aware Clustering (CAC), to find clusters that are well suited for being used as training datasets by classifiers for each underlying subpopulation.
After revision:  In this paper, we design a simple , efficient, and generic framework called Classification Aware Clustering (CAC), to find clusters that are well suited for being used as training datasets by classifiers for each underlying subpopulation.