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» The Combining Classifier: To Train or Not to Train
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IAT
2008
IEEE
13 years 11 months ago
A Personalized Spam Filtering Approach Utilizing Two Separately Trained Filters
By feeding personal e-mails into the training set, personalized content-based spam filters are believed to classify e-mails in higher accuracy. However, filters trained by both sp...
Wei-Lun Teng, Wei-Chung Teng
ICMCS
2006
IEEE
151views Multimedia» more  ICMCS 2006»
13 years 11 months ago
Support Vector Machine for Multiple Feature Classifcation
In this paper an effective method of using SVM classifier for multiple feature classification is proposed. Compared with traditional combination methods where all needed base clas...
Bing-Yu Sun, Moon-Chuen Lee
AAAI
2006
13 years 6 months ago
Multi-Conditional Learning: Generative/Discriminative Training for Clustering and Classification
This paper presents multi-conditional learning (MCL), a training criterion based on a product of multiple conditional likelihoods. When combining the traditional conditional proba...
Andrew McCallum, Chris Pal, Gregory Druck, Xuerui ...
SIGIR
2005
ACM
13 years 11 months ago
Automatic web query classification using labeled and unlabeled training data
Accurate topical categorization of user queries allows for increased effectiveness, efficiency, and revenue potential in general-purpose web search systems. Such categorization be...
Steven M. Beitzel, Eric C. Jensen, Ophir Frieder, ...
CVPR
2005
IEEE
14 years 7 months ago
Representational Oriented Component Analysis (ROCA) for Face Recognition with One Sample Image per Training Class
Subspace methods such as PCA, LDA, ICA have become a standard tool to perform visual learning and recognition. In this paper we propose Representational Oriented Component Analysi...
Fernando De la Torre, Ralph Gross, Simon Baker, B....