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» The Indifferent Naive Bayes Classifier
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PROMISE
2010
14 years 4 months ago
On the value of learning from defect dense components for software defect prediction
BACKGROUND: Defect predictors learned from static code measures can isolate code modules with a higher than usual probability of defects. AIMS: To improve those learners by focusi...
Hongyu Zhang, Adam Nelson, Tim Menzies
BIOINFORMATICS
2010
127views more  BIOINFORMATICS 2010»
14 years 9 months ago
Analyzing taxonomic classification using extensible Markov models
Motivation: As next generation sequencing is rapidly adding new genomes, their correct placement in the taxonomy needs verification. However, the current methods for confirming cl...
Rao M. Kotamarti, Michael Hahsler, Douglas Raiford...
ICCV
2003
IEEE
15 years 11 months ago
Minimally-Supervised Classification using Multiple Observation Sets
This paper discusses building complex classifiers from a single labeled example and vast number of unlabeled observation sets, each derived from observation of a single process or...
Chris Stauffer
ICML
2006
IEEE
15 years 10 months ago
The support vector decomposition machine
In machine learning problems with tens of thousands of features and only dozens or hundreds of independent training examples, dimensionality reduction is essential for good learni...
Francisco Pereira, Geoffrey J. Gordon
76
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ICML
2006
IEEE
15 years 10 months ago
Efficient lazy elimination for averaged one-dependence estimators
Semi-naive Bayesian classifiers seek to retain the numerous strengths of naive Bayes while reducing error by weakening the attribute independence assumption. Backwards Sequential ...
Fei Zheng, Geoffrey I. Webb