Music is considered as one the best form of expression of emotions. The music that people hear is governed by what mood they are in. The characteristics of music such as rhythm, melody, harmony, pitch, and timbre play a major role in human physiology and psychological functions, thus altering their mood. The Naive Bayes classifier is considered a popular classification technique in machine learning. It’s been shown to be very effective on a range of test data sets. However, the strong assumption that each attribute is independent of each other is often violated in real-world problems. In this paper, we have applied locally weighted Naïve Bayes to data stored within cloud to automate the process of classification of music.