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» Results of the KDD'99 Classifier Learning
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SDM
2010
SIAM
195views Data Mining» more  SDM 2010»
13 years 9 months ago
Adaptive Informative Sampling for Active Learning
Many approaches to active learning involve periodically training one classifier and choosing data points with the lowest confidence. An alternative approach is to periodically cho...
Zhenyu Lu, Xindong Wu, Josh Bongard
GECCO
2007
Springer
180views Optimization» more  GECCO 2007»
13 years 11 months ago
Support vector regression for classifier prediction
In this paper we introduce XCSF with support vector prediction: the problem of learning the prediction function is solved as a support vector regression problem and each classifie...
Daniele Loiacono, Andrea Marelli, Pier Luca Lanzi
CIKM
2006
Springer
13 years 11 months ago
A comparative study on classifying the functions of web page blocks
In this paper, we study the problem of learning block classification models to estimate block functions. We distinguish general models, which are learned across multiple sites, an...
Xiangye Xiao, Qiong Luo, Xing Xie, Wei-Ying Ma
IJCAI
1989
13 years 8 months ago
An Experimental Comparison of Symbolic and Connectionist Learning Algorithms
Despite the fact that many symbolic and connectionist (neural net) learning algorithms are addressing the same problem of learning from classified examples, very little Is known r...
Raymond J. Mooney, Jude W. Shavlik, Geoffrey G. To...
JMLR
2006
135views more  JMLR 2006»
13 years 7 months ago
Statistical Comparisons of Classifiers over Multiple Data Sets
While methods for comparing two learning algorithms on a single data set have been scrutinized for quite some time already, the issue of statistical tests for comparisons of more ...
Janez Demsar