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» Fast NML Computation for Naive Bayes Models
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DIS
2007
Springer
13 years 11 months ago
Fast NML Computation for Naive Bayes Models
Abstract. The Minimum Description Length (MDL) is an informationtheoretic principle that can be used for model selection and other statistical inference tasks. One way to implement...
Tommi Mononen, Petri Myllymäki
UAI
2003
13 years 6 months ago
Locally Weighted Naive Bayes
Despite its simplicity, the naive Bayes classifier has surprised machine learning researchers by exhibiting good performance on a variety of learning problems. Encouraged by thes...
Eibe Frank, Mark Hall, Bernhard Pfahringer
PAKDD
2010
ACM
212views Data Mining» more  PAKDD 2010»
13 years 9 months 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...
ICML
2005
IEEE
14 years 5 months ago
Naive Bayes models for probability estimation
Naive Bayes models have been widely used for clustering and classification. However, they are seldom used for general probabilistic learning and inference (i.e., for estimating an...
Daniel Lowd, Pedro Domingos
ICML
2003
IEEE
14 years 5 months ago
Tackling the Poor Assumptions of Naive Bayes Text Classifiers
Naive Bayes is often used as a baseline in text classification because it is fast and easy to implement. Its severe assumptions make such efficiency possible but also adversely af...
Jason D. Rennie, Lawrence Shih, Jaime Teevan, Davi...