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TNN
2010
154views Management» more  TNN 2010»
9 years 11 months ago
Discriminative semi-supervised feature selection via manifold regularization
We consider the problem of semi-supervised feature selection, where we are given a small amount of labeled examples and a large amount of unlabeled examples. Since a small number ...
Zenglin Xu, Irwin King, Michael R. Lyu, Rong Jin
ECAI
2010
Springer
10 years 1 months ago
Feature Selection by Approximating the Markov Blanket in a Kernel-Induced Space
The proposed feature selection method aims to find a minimum subset of the most informative variables for classification/regression by efficiently approximating the Markov Blanket ...
Qiang Lou, Zoran Obradovic
MICCAI
2010
Springer
10 years 2 months ago
Sparse Bayesian Learning for Identifying Imaging Biomarkers in AD Prediction
Abstract. We apply sparse Bayesian learning methods, automatic relevance determination (ARD) and predictive ARD (PARD), to Alzheimer’s disease (AD) classification to make accura...
Li Shen, Yuan Qi, Sungeun Kim, Kwangsik Nho, Jing ...
JUCS
2008
130views more  JUCS 2008»
10 years 4 months ago
Feature Selection for the Classification of Large Document Collections
: Feature selection methods are often applied in the context of document classification. They are particularly important for processing large data sets that may contain millions of...
Janez Brank, Dunja Mladenic, Marko Grobelnik, Nata...
BMCBI
2006
200views more  BMCBI 2006»
10 years 4 months ago
Comparison and evaluation of methods for generating differentially expressed gene lists from microarray data
Background: Numerous feature selection methods have been applied to the identification of differentially expressed genes in microarray data. These include simple fold change, clas...
Ian B. Jeffery, Desmond G. Higgins, Aedín C...
ESANN
2007
10 years 5 months ago
A new feature selection scheme using data distribution factor for transactional data
A new efficient unsupervised feature selection method is proposed to handle transactional data. The proposed feature selection method introduces a new Data Distribution Factor (DDF...
Piyang Wang, Tommy W. S. Chow
AUSDM
2008
Springer
271views Data Mining» more  AUSDM 2008»
10 years 6 months ago
Classification of Brain-Computer Interface Data
In this paper we investigate the classification of mental tasks based on electroencephalographic (EEG) data for Brain Computer Interfaces (BCI) in two scenarios: off line and on-l...
Omar AlZoubi, Irena Koprinska, Rafael A. Calvo
AAAI
2008
10 years 6 months ago
Concept-Based Feature Generation and Selection for Information Retrieval
Traditional information retrieval systems use query words to identify relevant documents. In difficult retrieval tasks, however, one needs access to a wealth of background knowled...
Ofer Egozi, Evgeniy Gabrilovich, Shaul Markovitch
AUSAI
2007
Springer
10 years 8 months ago
Building Classification Models from Microarray Data with Tree-Based Classification Algorithms
Building classification models plays an important role in DNA mircroarray data analyses. An essential feature of DNA microarray data sets is that the number of input variables (gen...
Peter J. Tan, David L. Dowe, Trevor I. Dix
ICML
2003
IEEE
10 years 9 months ago
An Evaluation on Feature Selection for Text Clustering
Feature selection methods have been successfully applied to text categorization but seldom applied to text clustering due to the unavailability of class label information. In this...
Tao Liu, Shengping Liu, Zheng Chen, Wei-Ying Ma
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