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ECML
1991
Springer
14 years 1 months ago
Semi-Naive Bayesian Classifier
1 A novel semi-naive Bayesian classifier is introduced that is particularly suitable to data with many attributes. The naive Bayesian classifier is taken as a starting point and co...
Igor Kononenko
IJAR
2010
105views more  IJAR 2010»
13 years 7 months ago
A tree augmented classifier based on Extreme Imprecise Dirichlet Model
In this paper we present TANC, i.e., a tree-augmented naive credal classifier based on imprecise probabilities; it models prior near-ignorance via the Extreme Imprecise Dirichlet ...
G. Corani, C. P. de Campos
JMLR
2006
132views more  JMLR 2006»
13 years 9 months ago
Learning to Detect and Classify Malicious Executables in the Wild
We describe the use of machine learning and data mining to detect and classify malicious executables as they appear in the wild. We gathered 1,971 benign and 1,651 malicious execu...
Jeremy Z. Kolter, Marcus A. Maloof
ICDM
2009
IEEE
151views Data Mining» more  ICDM 2009»
13 years 7 months ago
TagLearner: A P2P Classifier Learning System from Collaboratively Tagged Text Documents
The amount of text data on the Internet is growing at a very fast rate. Online text repositories for news agencies, digital libraries and other organizations currently store gigaan...
Haimonti Dutta, Xianshu Zhu, Tushar Mahule, Hillol...
VLSISP
2010
254views more  VLSISP 2010»
13 years 8 months ago
Manifold Based Local Classifiers: Linear and Nonlinear Approaches
Abstract In case of insufficient data samples in highdimensional classification problems, sparse scatters of samples tend to have many ‘holes’—regions that have few or no nea...
Hakan Cevikalp, Diane Larlus, Marian Neamtu, Bill ...