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» Results of the KDD'99 Classifier Learning
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ICML
2002
IEEE
14 years 8 months ago
Non-Disjoint Discretization for Naive-Bayes Classifiers
Previous discretization techniques have discretized numeric attributes into disjoint intervals. We argue that this is neither necessary nor appropriate for naive-Bayes classifiers...
Ying Yang, Geoffrey I. Webb
AMFG
2005
IEEE
293views Biometrics» more  AMFG 2005»
14 years 1 months ago
How to Train a Classifier Based on the Huge Face Database?
The development of web and digital camera nowadays has made it easier to collect more than hundreds of thousands of examples. How to train a face detector based on the collected en...
Jie Chen, Ruiping Wang, Shengye Yan, Shiguang Shan...
JMLR
2010
102views more  JMLR 2010»
13 years 2 months ago
Unsupervised Supervised Learning I: Estimating Classification and Regression Errors without Labels
Estimating the error rates of classifiers or regression models is a fundamental task in machine learning which has thus far been studied exclusively using supervised learning tech...
Pinar Donmez, Guy Lebanon, Krishnakumar Balasubram...
ICMCS
2006
IEEE
192views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Classifier Optimization for Multimedia Semantic Concept Detection
In this paper, we present an AUC (i.e., the Area Under the Curve of Receiver Operating Characteristics (ROC)) maximization based learning algorithm to design the classifier for ma...
Sheng Gao, Qibin Sun
GECCO
2006
Springer
173views Optimization» more  GECCO 2006»
13 years 11 months ago
Pareto-coevolutionary genetic programming classifier
The conversion and extension of the Incremental ParetoCoevolution Archive algorithm (IPCA) into the domain of Genetic Programming classifier evolution is presented. In order to ac...
Michal Lemczyk, Malcolm I. Heywood