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» Evaluating learning algorithms and classifiers
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DAWAK
2006
Springer
15 years 7 months ago
Learning Classifiers from Distributed, Ontology-Extended Data Sources
Abstract. There is an urgent need for sound approaches to integrative and collaborative analysis of large, autonomous (and hence, inevitably semantically heterogeneous) data source...
Doina Caragea, Jun Zhang 0002, Jyotishman Pathak, ...
ICPR
2010
IEEE
15 years 8 months ago
Microaneurysm (MA) Detection Via Sparse Representation Classifier with MA and Non-MA Dictionary Learning
Diabetic retinopathy (DR) is a common complication of diabetes that damages the retina and leads to sight loss if treated late. In its earliest stage, DR can be diagnosed by microa...
Bob Zhang, Lei Zhang, Jane You, Fakhri Karray
ICASSP
2008
IEEE
15 years 10 months ago
Ratio semi-definite classifiers
We present a novel classification model that is formulated as a ratio of semi-definite polynomials. We derive an efficient learning algorithm for this classifier, and apply it...
Jonathan Malkin, Jeff Bilmes
CEAS
2007
Springer
15 years 10 months ago
A Discriminative Classifier Learning Approach to Image Modeling and Spam Image Identification
We propose a discriminative classifier learning approach to image modeling for spam image identification. We analyze a large number of images extracted from the SpamArchive spam c...
Byungki Byun, Chin-Hui Lee, Steve Webb, Calton Pu
166
Voted
FLAIRS
2008
15 years 6 months ago
Evolutionary Learning of Dynamic Naive Bayesian Classifiers
Naive Bayesian classifiers work well in data sets with independent attributes. However, they perform poorly when the attributes are dependent or when there are one or more irrelev...
Miguel A. Palacios-Alonso, Carlos A. Brizuela, Lui...