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Computer-Executed Genre Identification of Music Alex Stabile

This example file demonstrates the computer-executed genre identification of music using a naïve Bayes classification algorithm. The classifier calculates the prior probability and frequency of labels in the training set to classify music genres based on features. However, issues arise when assuming independence of features and dealing with correlated features that can lead to high probabilities related to a particular label.

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Computer-Executed Genre Identification of Music Alex Stabile

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  1. Computer-Executed Genre Identification of Music Alex Stabile

  2. Example File http://www.ccarh.org/courses/253/files/midifiles-20080227-2up.pdf

  3. Naïve Bayes Classification http://nltk.googlecode.com/svn/trunk/doc/book/ch06.html

  4. Naïve Bayes Classifier • P: Prior Probability: frequency of a label in training set • P multiplied by percent of labels with particular feature

  5. Issues with classifier • “Naïve” - assumes that each feature is independent of the others • Correlated features cause excessively high probabilities of relating to a label

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