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» On Combining Classifiers
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PR
2006
83views more  PR 2006»
13 years 9 months ago
Optimal convex error estimators for classification
A cross-validation error estimator is obtained by repeatedly leaving out some data points, deriving classifiers on the remaining points, computing errors for these classifiers on ...
Chao Sima, Edward R. Dougherty
COST
2009
Springer
172views Multimedia» more  COST 2009»
13 years 6 months ago
Facial Expression Recognition Using Two-Class Discriminant Features
This paper presents a novel facial expression recognition methodology. In order to classify the expression of a test face to one of seven pre-determined facial expression classes, ...
Marios Kyperountas, Ioannis Pitas
KDD
2001
ACM
216views Data Mining» more  KDD 2001»
14 years 9 months ago
The distributed boosting algorithm
In this paper, we propose a general framework for distributed boosting intended for efficient integrating specialized classifiers learned over very large and distributed homogeneo...
Aleksandar Lazarevic, Zoran Obradovic
ICSE
2009
IEEE-ACM
14 years 9 months ago
Reasoning about edits to feature models
Features express the variabilities and commonalities among programs in a software product line (SPL). A feature model defines the valid combinations of features, where each combin...
Christian Kästner, Don S. Batory, Thomas Th&u...
ACL
2006
13 years 10 months ago
PCFGs with Syntactic and Prosodic Indicators of Speech Repairs
A grammatical method of combining two kinds of speech repair cues is presented. One cue, prosodic disjuncture, is detected by a decision tree-based ensemble classifier that uses a...
John Hale, Izhak Shafran, Lisa Yung, Bonnie J. Dor...