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» Messy Genetic Algorithms for Subset Feature Selection
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ACIVS
2009
Springer
15 years 9 months ago
Image Categorization Using ESFS: A New Embedded Feature Selection Method Based on SFS
Abstract. Feature subset selection is an important subject when training classifiers in Machine Learning (ML) problems. Too many input features in a ML problem may lead to the so-...
Huanzhang Fu, Zhongzhe Xiao, Emmanuel Dellandr&eac...
PAMI
2006
134views more  PAMI 2006»
15 years 2 months ago
A Genetic Algorithm Using Hyper-Quadtrees for Low-Dimensional K-means Clustering
The k-means algorithm is widely used for clustering because of its computational efficiency. Given n points in d-dimensional space and the number of desired clusters k, k-means see...
Michael Laszlo, Sumitra Mukherjee
ICIP
2010
IEEE
15 years 27 days ago
Robust object detection scheme using feature selection
Feature selection is an important issue for object detection. In this paper, we propose an effective wrapper-based feature selection scheme using Binary Particle Swarm Optimizatio...
Hong Pan, Liang-Zheng Xia, Truong Q. Nguyen
PRL
1998
132views more  PRL 1998»
15 years 2 months ago
Unsupervised feature selection using a neuro-fuzzy approach
A neuro-fuzzy methodology is described which involves connectionist minimization of a fuzzy feature evaluation index with unsupervised training. The concept of a ¯exible membersh...
Jayanta Basak, Rajat K. De, Sankar K. Pal
PAMI
2007
156views more  PAMI 2007»
15 years 2 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