This document proposes a two-stage approach to automatically identify emotions induced by Carnatic music using machine learning techniques. In the first classification stage, music samples are classified into emotional dimensions like devotion, pathos, and calmness. In the second clustering stage, music samples are grouped based on their emotional similarity as identified in the first stage. The results show some improvement over the baseline for classification but evaluations indicate that expanding the dataset with more labeled samples could further improve the accuracy of automatically identifying emotions in Carnatic music.