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» Evaluating learning algorithms and classifiers
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110
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FUIN
2010
268views more  FUIN 2010»
14 years 7 months ago
Boruta - A System for Feature Selection
Machine learning methods are often used to classify objects described by hundreds of attributes; in many applications of this kind a great fraction of attributes may be totally irr...
Miron B. Kursa, Aleksander Jankowski, Witold R. Ru...
110
Voted
FLAIRS
2008
15 years 2 months ago
Extending Nearest Neighbor Classification with Spheres of Confidence
The standard kNN algorithm suffers from two major drawbacks: sensitivity to the parameter value k, i.e., the number of neighbors, and the use of k as a global constant that is ind...
Ulf Johansson, Henrik Boström, Rikard Kö...
132
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AICS
2009
14 years 10 months ago
Analysis of the Effect of Unexpected Outliers in the Classification of Spectroscopy Data
Multi-class classification algorithms are very widely used, but we argue that they are not always ideal from a theoretical perspective, because they assume all classes are characte...
Frank G. Glavin, Michael G. Madden
EMNLP
2007
15 years 2 months ago
Online Learning for Deterministic Dependency Parsing
Deterministic parsing has emerged as an effective alternative for complex parsing algorithms which search the entire search space to get the best probable parse tree. In this pape...
Prashanth Mannem
ACCV
2010
Springer
14 years 7 months ago
Descriptor Learning Based on Fisher Separation Criterion for Texture Classification
Abstract. This paper proposes a novel method to deal with the representation issue in texture classification. A learning framework of image descriptor is designed based on the Fish...
Yimo Guo, Guoying Zhao, Matti Pietikäinen, Zh...