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KDD
2000
ACM
133views Data Mining» more  KDD 2000»
15 years 10 months ago
Data selection for support vector machine classifiers
The problem of extracting a minimal number of data points from a large dataset, in order to generate a support vector machine (SVM) classifier, is formulated as a concave minimiza...
Glenn Fung, Olvi L. Mangasarian
MCS
2010
Springer
15 years 8 months ago
Selecting Structural Base Classifiers for Graph-Based Multiple Classifier Systems
Selecting a set of good and diverse base classifiers is essential for building multiple classifier systems. However, almost all commonly used procedures for selecting such base cla...
Wan-Jui Lee, Robert P. W. Duin, Horst Bunke
ACG
2009
Springer
16 years 1 months ago
Plans, Patterns, and Move Categories Guiding a Highly Selective Search
In this paper we present our ideas for an Arimaa-playing program (also called a bot) that uses plans and pattern matching to guide a highly selective search. We restrict move gener...
Gerhard Trippen
IOLTS
2007
IEEE
120views Hardware» more  IOLTS 2007»
16 years 24 days ago
Accelerating Soft Error Rate Testing Through Pattern Selection
Soft error due to ionizing radiation is emerging as a major concern for future technologies. The measurement unit for failures due to soft errors is called Failure-In-Time (FIT) t...
Alodeep Sanyal, Kunal P. Ganeshpure, Sandip Kundu
CSB
2004
IEEE
135views Bioinformatics» more  CSB 2004»
15 years 10 months ago
Selection of Patient Samples and Genes for Outcome Prediction
Gene expression profiles with clinical outcome data enable monitoring of disease progression and prediction of patient survival at the molecular level. We present a new computatio...
Huiqing Liu, Jinyan Li, Limsoon Wong