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» Random subspace method for multivariate feature selection
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ICPR
2004
IEEE
15 years 11 months ago
Large Scale Feature Selection Using Modified Random Mutation Hill Climbing
Feature selection is a critical component of many pattern recognition applications. There are two distinct mechanisms for feature selection, namely the wrapper method and the filt...
Anil K. Jain, Michael E. Farmer, Shweta Bapna
CAIP
2001
Springer
293views Image Analysis» more  CAIP 2001»
15 years 2 months ago
A Markov Random Field Image Segmentation Model Using Combined Color and Texture Features
In this paper, we propose a Markov random field (MRF) image segmentation model which aims at combining color and texture features. The theoretical framework relies on Bayesian est...
Zoltan Kato, Ting-Chuen Pong
ESEM
2008
ACM
14 years 11 months ago
Fit data selection for software effort estimation models
To construct a better multivariate regression model for software effort estimation, this paper proposes a method to select projects as a fit data from a given project data set bas...
Koji Toda, Akito Monden, Ken-ichi Matsumoto
CRV
2005
IEEE
201views Robotics» more  CRV 2005»
15 years 3 months ago
Minimum Bayes Error Features for Visual Recognition by Sequential Feature Selection and Extraction
The extraction of optimal features, in a classification sense, is still quite challenging in the context of large-scale classification problems (such as visual recognition), inv...
Gustavo Carneiro, Nuno Vasconcelos
SLSFS
2005
Springer
15 years 3 months ago
Generalization Bounds for Subspace Selection and Hyperbolic PCA
We present a method which uses example pairs of equal or unequal class labels to select a subspace with near optimal metric properties in a kernel-induced Hilbert space. A represen...
Andreas Maurer