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» Boosting Methods for Regression
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146
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IEEECIT
2007
IEEE
15 years 9 months ago
Ensembles of Region Based Classifiers
In machine learning, ensemble classifiers have been introduced for more accurate pattern classification than single classifiers. We propose a new ensemble learning method that emp...
Sungha Choi, Byungwoo Lee, Jihoon Yang
ICDM
2003
IEEE
134views Data Mining» more  ICDM 2003»
15 years 8 months ago
Cost-Sensitive Learning by Cost-Proportionate Example Weighting
We propose and evaluate a family of methods for converting classifier learning algorithms and classification theory into cost-sensitive algorithms and theory. The proposed conve...
Bianca Zadrozny, John Langford, Naoki Abe
118
Voted
TKDE
2008
123views more  TKDE 2008»
15 years 2 months ago
Explaining Classifications For Individual Instances
We present a method for explaining predictions for individual instances. The presented approach is general and can be used with all classification models that output probabilities...
Marko Robnik-Sikonja, Igor Kononenko
126
Voted
IEICET
2010
124views more  IEICET 2010»
14 years 9 months ago
Fast Polar and Spherical Fourier Descriptors for Feature Extraction
Polar Fourier Descriptor(PFD) and Spherical Fourier Descriptor(SFD) are rotation invariant feature descriptors for two dimensional(2D) and three dimensional(3D) image retrieval an...
Zhuo Yang, Sei-ichiro Kamata
119
Voted
ICSE
2008
IEEE-ACM
16 years 3 months ago
Predicting accurate and actionable static analysis warnings: an experimental approach
Static analysis tools report software defects that may or may not be detected by other verification methods. Two challenges complicating the adoption of these tools are spurious f...
Joseph R. Ruthruff, John Penix, J. David Morgentha...