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ICCV
2011
IEEE
13 years 10 months ago
Informative Feature Selection for Object Recognition via Sparse PCA
Bag-of-words (BoW) methods are a popular class of object recognition methods that use image features (e.g., SIFT) to form visual dictionaries and subsequent histogram vectors to r...
Nikhil Naikal, Allen Y. Yang, S. Shankar Sastry
ICDM
2007
IEEE
129views Data Mining» more  ICDM 2007»
14 years 11 months ago
Feature Selection for Nonlinear Kernel Support Vector Machines
An easily implementable mixed-integer algorithm is proposed that generates a nonlinear kernel support vector machine (SVM) classifier with reduced input space features. A single ...
Olvi L. Mangasarian, Gang Kou
CIARP
2009
Springer
15 years 4 months ago
Analysis of the GRNs Inference by Using Tsallis Entropy and a Feature Selection Approach
Abstract. An important problem in the bioinformatics field is to understand how genes are regulated and interact through gene networks. This knowledge can be helpful for many appl...
Fabrício Martins Lopes, Evaldo A. de Olivei...
DOCENG
2006
ACM
15 years 4 months ago
NEWPAR: an automatic feature selection and weighting schema for category ranking
Category ranking provides a way to classify plain text documents into a pre-determined set of categories. This work proposes to have a look at typical document collections and ana...
Fernando Ruiz-Rico, José Luis Vicedo Gonz&a...
BMCBI
2007
173views more  BMCBI 2007»
14 years 10 months ago
Recursive Cluster Elimination (RCE) for classification and feature selection from gene expression data
Background: Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that a...
Malik Yousef, Segun Jung, Louise C. Showe, Michael...