PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Linear Programming Boosting for the Classification of Musical Genre
Tom Diethe and John Shawe-Taylor
In: NIPS 2007, 7-8 Dec 2007, Whistler, Canada.


area of music research, and as such provides a good starting point for testing a new algorithm. The Music Information Retrieval Evaluation eXchange (MIREX) is a yearly competition in a wide range of machine learning applications in music. MIREX 2005 included a genre classification task, the winner of which [1] was an application of the multiclass boosting algorithm AdaBoost.MH [2]. It is believed that Linear Programming Boosting (LPBoost) is a more appropriate algorithm for this application due to the higher degree of sparsity in the solutions [3]. The present study aims to improve on the [1] result by using a similar feature set and the multiclass boosting algorithm LPBoost.MC.

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EPrint Type:Conference or Workshop Item (Poster)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Brain Computer Interfaces
ID Code:3416
Deposited By:Tom Diethe
Deposited On:10 February 2008