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PKDD
2010
Springer
129views Data Mining» more  PKDD 2010»
15 years 1 months ago
Smarter Sampling in Model-Based Bayesian Reinforcement Learning
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
Pablo Samuel Castro, Doina Precup
AUSDM
2007
Springer
173views Data Mining» more  AUSDM 2007»
15 years 9 months ago
The Use of Various Data Mining and Feature Selection Methods in the Analysis of a Population Survey Dataset
This paper reports the results of feature reduction in the analysis of a population based dataset for which there were no specific target variables. All attributes were assessed a...
Ellen Pitt, Richi Nayak
WSDM
2010
ACM
245views Data Mining» more  WSDM 2010»
16 years 20 days ago
Improving Quality of Training Data for Learning to Rank Using Click-Through Data
In information retrieval, relevance of documents with respect to queries is usually judged by humans, and used in evaluation and/or learning of ranking functions. Previous work ha...
Jingfang Xu, Chuanliang Chen, Gu Xu, Hang Li, Elbi...
ICDM
2002
IEEE
143views Data Mining» more  ICDM 2002»
15 years 8 months ago
A Hybrid Approach to Discover Bayesian Networks From Databases Using Evolutionary Programming
This paper describes a novel data mining approach that employs evolutionary programming to discover knowledge represented in Bayesian networks. There are two different approaches ...
Man Leung Wong, Shing Yan Lee, Kwong-Sak Leung
SIGKDD
2008
150views more  SIGKDD 2008»
15 years 3 months ago
Learning to improve area-under-FROC for imbalanced medical data classification using an ensemble method
This paper presents our solution for KDD Cup 2008 competition that aims at optimizing the area under ROC for breast cancer detection. We exploited weighted-based classification me...
Hung-Yi Lo, Chun-Min Chang, Tsung-Hsien Chiang, Ch...