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PAMI
2007
156views more  PAMI 2007»
13 years 7 months ago
Selection and Fusion of Color Models for Image Feature Detection
—The choice of a color model is of great importance for many computer vision algorithms (e.g., feature detection, object recognition, and tracking) as the chosen color model indu...
Harro M. G. Stokman, Theo Gevers
ICML
2001
IEEE
14 years 8 months ago
Filters, Wrappers and a Boosting-Based Hybrid for Feature Selection
In this paper, we examine the advantages and disadvantages of filter and wrapper methods for feature selection and propose a new hybrid algorithm that uses boosting and incorporat...
Sanmay Das
ICML
2000
IEEE
14 years 8 months ago
Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning
Algorithms for feature selection fall into two broad categories: wrappers that use the learning algorithm itself to evaluate the usefulness of features and filters that evaluate f...
Mark A. Hall
EC
2007
167views ECommerce» more  EC 2007»
13 years 7 months ago
Comparison-Based Algorithms Are Robust and Randomized Algorithms Are Anytime
Randomized search heuristics (e.g., evolutionary algorithms, simulated annealing etc.) are very appealing to practitioners, they are easy to implement and usually provide good per...
Sylvain Gelly, Sylvie Ruette, Olivier Teytaud
PAMI
2007
102views more  PAMI 2007»
13 years 7 months ago
Feature Subset Selection and Ranking for Data Dimensionality Reduction
—A new unsupervised forward orthogonal search (FOS) algorithm is introduced for feature selection and ranking. In the new algorithm, features are selected in a stepwise way, one ...
Hua-Liang Wei, Stephen A. Billings