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» Classifier Selection Based on Data Complexity Measures
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SDM
2008
SIAM
157views Data Mining» more  SDM 2008»
13 years 8 months ago
ROC-tree: A Novel Decision Tree Induction Algorithm Based on Receiver Operating Characteristics to Classify Gene Expression Data
Gene expression information from microarray experiments is a primary form of data for biological analysis and can offer insights into disease processes and cellular behaviour. Suc...
M. Maruf Hossain, Md. Rafiul Hassan, James Bailey
MCS
2010
Springer
13 years 9 months ago
Dynamic Selection of Ensembles of Classifiers Using Contextual Information
In a multiple classifier system, dynamic selection (DS) has been used successfully to choose only the best subset of classifiers to recognize the test samples. Dos Santos et al...
Paulo Rodrigo Cavalin, Robert Sabourin, Ching Y. S...
BIB
2011
12 years 11 months ago
Using cross-validation to evaluate predictive accuracy of survival risk classifiers based on high-dimensional data
Developments in whole genome biotechnology have stimulated statistical focus on prediction methods. We review here methodology for classifying patients into survival risk groups a...
Richard M. Simon, Jyothi Subramanian, Ming-Chung L...
ISNN
2010
Springer
13 years 5 months ago
Extension of the Generalization Complexity Measure to Real Valued Input Data Sets
Abstract. This paper studies the extension of the Generalization Complexity (GC) measure to real valued input problems. The GC measure, defined in Boolean space, was proposed as a...
Iván Gómez, Leonardo Franco, Jos&eac...
AI
2001
Springer
13 years 12 months ago
Learning Bayesian Belief Network Classifiers: Algorithms and System
Abstract. This paper investigates the methods for learning predictive classifiers based on Bayesian belief networks (BN) – primarily unrestricted Bayesian networks and Bayesian m...
Jie Cheng, Russell Greiner