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BMCBI
2006
110views more  BMCBI 2006»
13 years 7 months ago
Bias in error estimation when using cross-validation for model selection
Background: Cross-validation (CV) is an effective method for estimating the prediction error of a classifier. Some recent articles have proposed methods for optimizing classifiers...
Sudhir Varma, Richard Simon
COLING
2002
13 years 7 months ago
Efficient Support Vector Classifiers for Named Entity Recognition
Named Entity (NE) recognition is a task in which proper nouns and numerical information are extracted from documents and are classified into categories such as person, organizatio...
Hideki Isozaki, Hideto Kazawa
JMM2
2008
124views more  JMM2 2008»
13 years 7 months ago
Integrated Feature Selection and Clustering for Taxonomic Problems within Fish Species Complexes
As computer and database technologies advance rapidly, biologists all over the world can share biologically meaningful data from images of specimens and use the data to classify th...
Huimin Chen, Henry L. Bart Jr., Shuqing Huang
GRC
2010
IEEE
13 years 5 months ago
A Comparative Study of Threshold-Based Feature Selection Techniques
Given high-dimensional software measurement data, researchers and practitioners often use feature (metric) selection techniques to improve the performance of software quality clas...
Huanjing Wang, Taghi M. Khoshgoftaar, Jason Van Hu...
ICML
2004
IEEE
14 years 8 months ago
Margin based feature selection - theory and algorithms
Feature selection is the task of choosing a small set out of a given set of features that capture the relevant properties of the data. In the context of supervised classification ...
Ran Gilad-Bachrach, Amir Navot, Naftali Tishby