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» Transfer Learning in Decision Trees
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AAAI
2006
13 years 9 months ago
A Fast Decision Tree Learning Algorithm
There is growing interest in scaling up the widely-used decision-tree learning algorithms to very large data sets. Although numerous diverse techniques have been proposed, a fast ...
Jiang Su, Harry Zhang
ICML
1999
IEEE
14 years 8 months ago
Lazy Bayesian Rules: A Lazy Semi-Naive Bayesian Learning Technique Competitive to Boosting Decision Trees
Lbr is a lazy semi-naive Bayesian classi er learning technique, designed to alleviate the attribute interdependence problem of naive Bayesian classi cation. To classify a test exa...
Zijian Zheng, Geoffrey I. Webb, Kai Ming Ting
PAKDD
2010
ACM
212views Data Mining» more  PAKDD 2010»
14 years 17 days ago
Fast Perceptron Decision Tree Learning from Evolving Data Streams
Abstract. Mining of data streams must balance three evaluation dimensions: accuracy, time and memory. Excellent accuracy on data streams has been obtained with Naive Bayes Hoeffdi...
Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer...
BMCBI
2006
72views more  BMCBI 2006»
13 years 7 months ago
Selecting effective siRNA sequences by using radial basis function network and decision tree learning
Background: Although short interfering RNA (siRNA) has been widely used for studying gene functions in mammalian cells, its gene silencing efficacy varies markedly and there are o...
Shigeru Takasaki, Yoshihiro Kawamura, Akihiko Kona...
IRI
2008
IEEE
14 years 2 months ago
Compound record clustering algorithm for design pattern detection by decision tree learning
Recovering design patterns applied in a system can help refactoring the system. Machine learning algorithms have been successfully applied in mining data patterns. However, one of...
Jing Dong, Yongtao Sun, Yajing Zhao