TY - GEN
T1 - Online feature selection algorithm with bayesian ℓ 1 regularization
AU - Cai, Yunpeng
AU - Sun, Yijun
AU - Li, Jian
AU - Goodison, Steve
PY - 2009
Y1 - 2009
N2 - We propose a novel online-learning based feature selection algorithm for supervised learning in the presence of a huge amount of irrelevant features. The key idea of the algorithm is to decompose a nonlinear problem into a set of locally linear ones through local learning, and then estimate the relevance of features globally in a large margin framework with ℓ1 regularization. Unlike batch learning, the regularization parameter in online learning has to be tuned on-thefly with the increasing of training data. We address this issue within the Bayesian learning paradigm, and provide an analytic solution for automatic estimation of the regularization parameter via variational methods. Numerical experiments on a variety of benchmark data sets are presented that demonstrate the effectiveness of the newly proposed feature selection algorithm.
AB - We propose a novel online-learning based feature selection algorithm for supervised learning in the presence of a huge amount of irrelevant features. The key idea of the algorithm is to decompose a nonlinear problem into a set of locally linear ones through local learning, and then estimate the relevance of features globally in a large margin framework with ℓ1 regularization. Unlike batch learning, the regularization parameter in online learning has to be tuned on-thefly with the increasing of training data. We address this issue within the Bayesian learning paradigm, and provide an analytic solution for automatic estimation of the regularization parameter via variational methods. Numerical experiments on a variety of benchmark data sets are presented that demonstrate the effectiveness of the newly proposed feature selection algorithm.
UR - https://www.scopus.com/pages/publications/67650661623
U2 - 10.1007/978-3-642-01307-2_37
DO - 10.1007/978-3-642-01307-2_37
M3 - Conference contribution
AN - SCOPUS:67650661623
SN - 3642013066
SN - 9783642013065
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 401
EP - 413
BT - 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2009
T2 - 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2009
Y2 - 27 April 2009 through 30 April 2009
ER -