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BIOINFORMATICS
2006
92views more  BIOINFORMATICS 2006»
13 years 8 months ago
What should be expected from feature selection in small-sample settings
Motivation: High-throughput technologies for rapid measurement of vast numbers of biological variables offer the potential for highly discriminatory diagnosis and prognosis; howev...
Chao Sima, Edward R. Dougherty
SDM
2009
SIAM
205views Data Mining» more  SDM 2009»
14 years 5 months ago
Identifying Information-Rich Subspace Trends in High-Dimensional Data.
Identifying information-rich subsets in high-dimensional spaces and representing them as order revealing patterns (or trends) is an important and challenging research problem in m...
Chandan K. Reddy, Snehal Pokharkar
ESWA
2007
151views more  ESWA 2007»
13 years 8 months ago
A novel feature selection algorithm for text categorization
With the development of the web, large numbers of documents are available on the Internet. Digital libraries, news sources and inner data of companies surge more and more. Automat...
Wenqian Shang, Houkuan Huang, Haibin Zhu, Yongmin ...
KDD
2004
ACM
151views Data Mining» more  KDD 2004»
14 years 9 months ago
Feature selection in scientific applications
Numerous applications of data mining to scientific data involve the induction of a classification model. In many cases, the collection of data is not performed with this task in m...
Erick Cantú-Paz, Shawn Newsam, Chandrika Ka...
ICPR
2006
IEEE
14 years 9 months ago
Finding Rule Groups to Classify High Dimensional Gene Expression Datasets
Microarray data provides quantitative information about the transcription profile of cells. To analyze microarray datasets, methodology of machine learning has increasingly attrac...
Jiyuan An, Yi-Ping Phoebe Chen