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AAAI
2006
14 years 11 months ago
Efficient L1 Regularized Logistic Regression
L1 regularized logistic regression is now a workhorse of machine learning: it is widely used for many classification problems, particularly ones with many features. L1 regularized...
Su-In Lee, Honglak Lee, Pieter Abbeel, Andrew Y. N...
ML
2002
ACM
127views Machine Learning» more  ML 2002»
14 years 9 months ago
Sparse Regression Ensembles in Infinite and Finite Hypothesis Spaces
We examine methods for constructing regression ensembles based on a linear program (LP). The ensemble regression function consists of linear combinations of base hypotheses generat...
Gunnar Rätsch, Ayhan Demiriz, Kristin P. Benn...
ML
2006
ACM
132views Machine Learning» more  ML 2006»
14 years 9 months ago
A suffix tree approach to anti-spam email filtering
We present an approach to email filtering based on the suffix tree data structure. A method for the scoring of emails using the suffix tree is developed and a number of scoring and...
Rajesh Pampapathi, Boris Mirkin, Mark Levene
SGAI
2010
Springer
14 years 7 months ago
Induction of Modular Classification Rules: Using Jmax-pruning
The Prism family of algorithms induces modular classification rules which, in contrast to decision tree induction algorithms, do not necessarily fit together into a decision tree s...
Frederic T. Stahl, Max Bramer
COLT
2007
Springer
15 years 1 months ago
Robust Reductions from Ranking to Classification
Abstract. We reduce ranking, as measured by the Area Under the Receiver Operating Characteristic Curve (AUC), to binary classification. The core theorem shows that a binary classif...
Maria-Florina Balcan, Nikhil Bansal, Alina Beygelz...