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» Classifier Selection Based on Data Complexity Measures
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KDD
1998
ACM
442views Data Mining» more  KDD 1998»
13 years 11 months ago
BAYDA: Software for Bayesian Classification and Feature Selection
BAYDA is a software package for flexible data analysis in predictive data mining tasks. The mathematical model underlying the program is based on a simple Bayesian network, the Na...
Petri Kontkanen, Petri Myllymäki, Tomi Siland...
GRC
2008
IEEE
13 years 8 months ago
Fuzzy Entropy based Max-Relevancy and Min-Redundancy Feature Selection
Feature selection is an important problem for pattern classification systems. Mutual information is a good indicator of relevance between variables, and has been used as a measure...
Shuang An, Qinghua Hu, Daren Yu
MCS
2007
Springer
14 years 1 months ago
Random Feature Subset Selection for Ensemble Based Classification of Data with Missing Features
Abstract. We report on our recent progress in developing an ensemble of classifiers based algorithm for addressing the missing feature problem. Inspired in part by the random subsp...
Joseph DePasquale, Robi Polikar
KDD
2004
ACM
139views Data Mining» more  KDD 2004»
14 years 7 months ago
Learning a complex metabolomic dataset using random forests and support vector machines
Metabolomics is the omics science of biochemistry. The associated data include the quantitative measurements of all small molecule metabolites in a biological sample. These datase...
Young Truong, Xiaodong Lin, Chris Beecher
ICPR
2000
IEEE
14 years 8 months ago
Measuring the Complexity of Classification Problems
We studied a number of measures that characterize the difficulty of a classification problem. We compared a set of real world problems to random combinations of points in this mea...
Tin Kam Ho, Mitra Basu