There are several research work is in progress in the direction of raag detection. Ragas are specific to the time of the day and it generates a specific sentiment only when played at the right time. It is the unique sequence in music which comprises of five to nine musical notes in melodic music. It depends on the pitch of musical notes and the mood in which they are conveyed rather than the sequence of notes. Its accurate detection is helpful in generating correct and accurate raag with the different musical instrument. There are several obstacles in accurate raag detection technique. The major challenges are the complex parameters like pitch and mood in the music, skipping extra tones, conversion of different data attributes and raag tempo. In this paper a study and analysis have been presented to stumble the gaps and finding the advantages of the previous approaches. The previous research suggests supervised and unsupervised learning both for raag detection. So this paper included the methods from above two for comparison. This study shows that the supervised learning is capable in improving the detection results.