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  was an
application of the multiclass boosting algorithm AdaBoost.MH . 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 . The
present study aims to improve on the  result by using a similar feature set and
the multiclass boosting algorithm LPBoost.MC.
|EPrint Type:||Conference or Workshop Item (Poster)|
|Project Keyword:||Project Keyword UNSPECIFIED|
|Subjects:||Brain Computer Interfaces|
|Deposited By:||Tom Diethe|
|Deposited On:||10 February 2008|