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» An Experimental Study on Feature Subset Selection Methods
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KDD
2005
ACM
205views Data Mining» more  KDD 2005»
15 years 9 months ago
Feature bagging for outlier detection
Outlier detection has recently become an important problem in many industrial and financial applications. In this paper, a novel feature bagging approach for detecting outliers in...
Aleksandar Lazarevic, Vipin Kumar
JMLR
2011
192views more  JMLR 2011»
14 years 10 months ago
Minimum Description Length Penalization for Group and Multi-Task Sparse Learning
We propose a framework MIC (Multiple Inclusion Criterion) for learning sparse models based on the information theoretic Minimum Description Length (MDL) principle. MIC provides an...
Paramveer S. Dhillon, Dean P. Foster, Lyle H. Unga...
ICASSP
2011
IEEE
14 years 7 months ago
Nonparametric Bayesian feature selection for multi-task learning
We present a nonparametric Bayesian model for multi-task learning, with a focus on feature selection in binary classification. The model jointly identifies groups of similar tas...
Hui Li, Xuejun Liao, Lawrence Carin
GFKL
2004
Springer
97views Data Mining» more  GFKL 2004»
15 years 9 months ago
Experimental Design for Variable Selection in Data Bases
This paper analyses the influence of 13 stylized facts of the German economy on the West German business cycles from 1955 to 1994. The method used in this investigation is Statist...
Constanze Pumplün, Claus Weihs, Andrea Preuss...
ICB
2007
Springer
185views Biometrics» more  ICB 2007»
15 years 10 months ago
Biometric Hashing Based on Genetic Selection and Its Application to On-Line Signatures
We present a general biometric hash generation scheme based on vector quantization of multiple feature subsets selected with genetic optimization. The quantization of subsets overc...
Manuel R. Freire, Julian Fiérrez-Aguilar, J...