Sciweavers

1037 search results - page 78 / 208
» Learning of Boolean Functions Using Support Vector Machines
Sort
View
ICML
2007
IEEE
14 years 9 months ago
Sparse probabilistic classifiers
The scores returned by support vector machines are often used as a confidence measures in the classification of new examples. However, there is no theoretical argument sustaining ...
Romain Hérault, Yves Grandvalet
ICML
2003
IEEE
14 years 9 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...
PAKDD
2005
ACM
102views Data Mining» more  PAKDD 2005»
14 years 2 months ago
Automatic Occupation Coding with Combination of Machine Learning and Hand-Crafted Rules
Abstract. We apply a machine learning method to the occupation coding, which is a task to categorize the answers to open-ended questions regarding the respondent’s occupation. Sp...
Kazuko Takahashi, Hiroya Takamura, Manabu Okumura
APBC
2003
128views Bioinformatics» more  APBC 2003»
13 years 10 months ago
Machine Learning in DNA Microarray Analysis for Cancer Classification
The development of microarray technology has supplied a large volume of data to many fields. In particular, it has been applied to prediction and diagnosis of cancer, so that it e...
Sung-Bae Cho, Hong-Hee Won
PKDD
2009
Springer
88views Data Mining» more  PKDD 2009»
14 years 3 months ago
Feature Weighting Using Margin and Radius Based Error Bound Optimization in SVMs
The Support Vector Machine error bound is a function of the margin and radius. Standard SVM algorithms maximize the margin within a given feature space, therefore the radius is fi...
Huyen Do, Alexandros Kalousis, Melanie Hilario