Sciweavers

PPSN
2010
Springer
13 years 2 months ago
Feature Selection for Multi-purpose Predictive Models: A Many-Objective Task
The target of machine learning is a predictive model that performs well on unseen data. Often, such a model has multiple intended uses, related to different points in the tradeoff ...
Alan P. Reynolds, David W. Corne, Michael J. Chant...
PVLDB
2008
82views more  PVLDB 2008»
13 years 4 months ago
Mining non-redundant high order correlations in binary data
Many approaches have been proposed to find correlations in binary data. Usually, these methods focus on pair-wise correlations. In biology applications, it is important to find co...
Xiang Zhang, Feng Pan, Wei Wang 0010, Andrew B. No...
TNN
2008
133views more  TNN 2008»
13 years 4 months ago
A General Wrapper Approach to Selection of Class-Dependent Features
In this paper, we argue that for a C-class classification problem, C 2-class classifiers, each of which discriminating one class from the other classes and having a characteristic ...
Lipo Wang, Nina Zhou, Feng Chu
CIBCB
2006
IEEE
13 years 6 months ago
A New Hybrid Approach for Unsupervised Gene Selection
In recent years, unsupervised gene (feature) selection has become an integral part of microarray analysis because of the large number of genes and complexity in biological systems....
Young Bun Kim, Jean Gao
KDD
1995
ACM
133views Data Mining» more  KDD 1995»
13 years 8 months ago
Feature Subset Selection Using the Wrapper Method: Overfitting and Dynamic Search Space Topology
In the wrapperapproachto feature subset selection, a searchfor an optimalset of features is madeusingthe induction algorithm as a black box. Theestimated future performanceof the ...
Ron Kohavi, Dan Sommerfield
PAKDD
2000
ACM
124views Data Mining» more  PAKDD 2000»
13 years 8 months ago
Feature Selection for Clustering
In clustering, global feature selection algorithms attempt to select a common feature subset that is relevant to all clusters. Consequently, they are not able to identify individu...
Manoranjan Dash, Huan Liu
CIARP
2006
Springer
13 years 8 months ago
Oscillating Feature Subset Search Algorithm for Text Categorization
Abstract. A major characteristic of text document categorization problems is the extremely high dimensionality of text data. In this paper we explore the usability of the Oscillati...
Jana Novovicová, Petr Somol, Pavel Pudil
GECCO
1999
Springer
133views Optimization» more  GECCO 1999»
13 years 8 months ago
Non-Standard Crossover for a Standard Representation - Commonality-Based Feature Subset Selection
The Commonality-Based Crossover Framework has been presented as a general model for designing problem specific operators. Following this model, the Common Features/Random Sample ...
Stephen Y. Chen, Cesar Guerra-Salcedo, Stephen F. ...
GECCO
2004
Springer
144views Optimization» more  GECCO 2004»
13 years 10 months ago
Feature Subset Selection, Class Separability, and Genetic Algorithms
Abstract. The performance of classification algorithms in machine learning is affected by the features used to describe the labeled examples presented to the inducers. Therefore,...
Erick Cantú-Paz
ICIP
2003
IEEE
14 years 6 months ago
Feature selection for unsupervised discovery of statistical temporal structures in video
We present algorithms for automatic feature selection for unsupervised structure discovery from video sequences. Feature selection in this scenario is hard because of the absence ...
Lexing Xie, Shih-Fu Chang, Ajay Divakaran, Huifang...