PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Linear Programming Boosting for Uneven Datasets
Jure Leskovec and John Shawe-Taylor
In: Learning Methods for Text Understanding and Mining, 26 - 29 January 2004, Grenoble, France.


The paper extends the notion of linear programming boosting to handle uneven datasets. Extensive experiments with text classification problem compare the performance of a number of different boosting strategies, concentrating on the problems posed by uneven datasets.

PDF - Requires Adobe Acrobat Reader or other PDF viewer.
EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Theory & Algorithms
Information Retrieval & Textual Information Access
ID Code:19
Deposited By:Steve Gunn
Deposited On:09 May 2004