TY - JOUR
T1 - Fast iterative mining using sparsity-inducing loss functions
AU - Saigo, Hiroto
AU - Kashima, Hisashi
AU - Tsuda, Koji
PY - 2013
Y1 - 2013
N2 - Apriori-based mining algorithms enumerate frequent patterns efficiently, but the resulting large number of patterns makes it difficult to directly apply subsequent learning tasks. Recently, efficient iterative methods are proposed for mining discriminative patterns for classification and regression. These methods iteratively execute discriminative pattern mining algorithm and update example weights to emphasize on examples which received large errors in the previous iteration. In this paper, we study a family of loss functions that induces sparsity on example weights. Most of the resulting example weights become zeros, so we can eliminate those examples from discriminative pattern mining, leading to a significant decrease in search space and time. In computational experiments we compare and evaluate various loss functions in terms of the amount of sparsity induced and resulting speed-up obtained.
AB - Apriori-based mining algorithms enumerate frequent patterns efficiently, but the resulting large number of patterns makes it difficult to directly apply subsequent learning tasks. Recently, efficient iterative methods are proposed for mining discriminative patterns for classification and regression. These methods iteratively execute discriminative pattern mining algorithm and update example weights to emphasize on examples which received large errors in the previous iteration. In this paper, we study a family of loss functions that induces sparsity on example weights. Most of the resulting example weights become zeros, so we can eliminate those examples from discriminative pattern mining, leading to a significant decrease in search space and time. In computational experiments we compare and evaluate various loss functions in terms of the amount of sparsity induced and resulting speed-up obtained.
UR - http://www.scopus.com/inward/record.url?scp=84882696948&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84882696948&partnerID=8YFLogxK
U2 - 10.1587/transinf.E96.D.1766
DO - 10.1587/transinf.E96.D.1766
M3 - Article
AN - SCOPUS:84882696948
VL - E96-D
SP - 1766
EP - 1773
JO - IEICE Transactions on Information and Systems
JF - IEICE Transactions on Information and Systems
SN - 0916-8532
IS - 8
ER -