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» Classifier Selection Based on Data Complexity Measures
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ICML
2004
IEEE
16 years 2 months ago
Margin based feature selection - theory and algorithms
Feature selection is the task of choosing a small set out of a given set of features that capture the relevant properties of the data. In the context of supervised classification ...
Ran Gilad-Bachrach, Amir Navot, Naftali Tishby
AAAI
1997
15 years 2 months ago
Applications of Rule-Base Coverage Measures to Expert System Evaluation
Often a rule-based system is tested by checking its performance on a number of test cases with known solutions, modifying the system until it gives the correct results for all or ...
Valerie Barr
ICMLC
2010
Springer
14 years 11 months ago
Optimization of bagging classifiers based on SBCB algorithm
: Bagging (Bootstrap Aggregating) has been proved to be a useful, effective and simple ensemble learning methodology. In generic bagging methods, all the classifiers which are trai...
Xiao-Dong Zeng, Sam Chao, Fai Wong
ACL
2009
14 years 11 months ago
A Framework of Feature Selection Methods for Text Categorization
In text categorization, feature selection (FS) is a strategy that aims at making text classifiers more efficient and accurate. However, when dealing with a new task, it is still d...
Shoushan Li, Rui Xia, Chengqing Zong, Chu-Ren Huan...
BMCBI
2006
165views more  BMCBI 2006»
15 years 1 months ago
A stable gene selection in microarray data analysis
Background: Microarray data analysis is notorious for involving a huge number of genes compared to a relatively small number of samples. Gene selection is to detect the most signi...
Kun Yang, Zhipeng Cai, Jianzhong Li, Guohui Lin