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JAIR
2006
113views more  JAIR 2006»
13 years 8 months ago
Generative Prior Knowledge for Discriminative Classification
We present a novel framework for integrating prior knowledge into discriminative classifiers. Our framework allows discriminative classifiers such as Support Vector Machines (SVMs...
Arkady Epshteyn, Gerald DeJong
JCP
2006
102views more  JCP 2006»
13 years 8 months ago
Efficient Formulations for 1-SVM and their Application to Recommendation Tasks
The present paper proposes new approaches for recommendation tasks based on one-class support vector machines (1-SVMs) with graph kernels generated from a Laplacian matrix. We intr...
Yasutoshi Yajima, Tien-Fang Kuo
NECO
2008
112views more  NECO 2008»
13 years 8 months ago
Second-Order SMO Improves SVM Online and Active Learning
Iterative learning algorithms that approximate the solution of support vector machines (SVMs) have two potential advantages. First, they allow for online and active learning. Seco...
Tobias Glasmachers, Christian Igel
IJISTA
2007
124views more  IJISTA 2007»
13 years 8 months ago
Incremental learning for spoken affect classification and its application in call-centres
: This paper introduces a system for real-time incremental learning in a call-centre environment. The classifier used is a Support Vector Machine (SVM) and it is applied to telepho...
Donn Morrison, Ruili Wang, W. L. Xu, Liyanage C. D...
TKDE
2008
123views more  TKDE 2008»
13 years 8 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