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» Evaluating learning algorithms and classifiers
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BMCBI
2006
164views more  BMCBI 2006»
15 years 4 months ago
Evaluation of clustering algorithms for gene expression data
Background: Cluster analysis is an integral part of high dimensional data analysis. In the context of large scale gene expression data, a filtered set of genes are grouped togethe...
Susmita Datta, Somnath Datta
ICML
2005
IEEE
16 years 5 months ago
Explanation-Augmented SVM: an approach to incorporating domain knowledge into SVM learning
We introduce a novel approach to incorporating domain knowledge into Support Vector Machines to improve their example efficiency. Domain knowledge is used in an Explanation Based ...
Qiang Sun, Gerald DeJong
JMLR
2008
117views more  JMLR 2008»
15 years 4 months ago
Active Learning by Spherical Subdivision
We introduce a computationally feasible, "constructive" active learning method for binary classification. The learning algorithm is initially formulated for separable cl...
Falk-Florian Henrich, Klaus Obermayer
ICDAR
1999
IEEE
15 years 9 months ago
Cursive Character Detection using Incremental Learning
This paper describes a new hybrid architecture for an artificial neural network classifier that enables incremental learning. The learning algorithm of the proposed architecture d...
Jean-François Hébert, Marc Parizeau,...
EACL
2003
ACL Anthology
15 years 6 months ago
Learning to Identify Fragmented Words in Spoken Discourse
Disfluent speech adds to the difficulty of processing spoken language utterances. In this paper we concentrate on identifying one disfluency phenomenon: fragmented words. Our d...
Piroska Lendvai