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PKDD
2009
Springer
152views Data Mining» more  PKDD 2009»
14 years 2 months ago
Feature Selection for Value Function Approximation Using Bayesian Model Selection
Abstract. Feature selection in reinforcement learning (RL), i.e. choosing basis functions such that useful approximations of the unkown value function can be obtained, is one of th...
Tobias Jung, Peter Stone
CAINE
2008
13 years 9 months ago
Hierarchical Clustering of Features on Categorical Data of Biomedical Applications
Data mining became increasingly important in bioinformatics and biomedical area during last decade. Various data mining methods, such as association rule mining and clustering, ha...
Yi Lu, Lily R. Liang
AUSDM
2006
Springer
122views Data Mining» more  AUSDM 2006»
13 years 11 months ago
Analysis of Breast Feeding Data Using Data Mining Methods
The purpose of this study is to demonstrate the benefit of using common data mining techniques on survey data where statistical analysis is routinely applied. The statistical surv...
Hongxing He, Huidong Jin, Jie Chen, Damien McAulla...
KDD
2012
ACM
178views Data Mining» more  KDD 2012»
11 years 10 months ago
Mining emerging patterns by streaming feature selection
Building an accurate emerging pattern classifier with a highdimensional dataset is a challenging issue. The problem becomes even more difficult if the whole feature space is unava...
Kui Yu, Wei Ding 0003, Dan A. Simovici, Xindong Wu
ICMCS
2006
IEEE
112views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Visual Feature Space Analysis for Unsupervised Effectiveness Estimation and Feature Engineering
The Feature Vector approach is one of the most popular schemes for managing multimedia data. For many data types such as audio, images, or 3D models, an abundance of different Fea...
Tobias Schreck, Daniel A. Keim, Christian Panse