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» Temporal Data Classification Using Linear Classifiers
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IPPS
1999
IEEE
15 years 6 months ago
Parallel Out-of-Core Divide-and-Conquer Techniques with Application to Classification Trees
Classification is an important problem in the field of data mining. Construction of good classifiers is computationally intensive and offers plenty of scope for parallelization. D...
Mahesh K. Sreenivas, Khaled Alsabti, Sanjay Ranka
SSPR
2004
Springer
15 years 7 months ago
An MCMC Feature Selection Technique for Characterizing and Classifying Spatial Region Data
We focus on characterizing spatial region data when distinct classes of structural patterns are present. We propose a novel statistical approach based on a supervised framework for...
Despina Kontos, Vasileios Megalooikonomou, Marc J....
FUIN
2002
123views more  FUIN 2002»
15 years 2 months ago
Learning Rough Set Classifiers from Gene Expressions and Clinical Data
Biological research is currently undergoing a revolution. With the advent of microarray technology the behavior of thousands of genes can be measured simultaneously. This capabilit...
Herman Midelfart, Henryk Jan Komorowski, Kristin N...
CVPR
2007
IEEE
16 years 4 months ago
A Nonparametric Treatment for Location/Segmentation Based Visual Tracking
In this paper, we address two closely related visual tracking problems: 1) localizing a target's position in low or moderate resolution videos and 2) segmenting a target'...
Le Lu, Gregory D. Hager
KDD
2006
ACM
179views Data Mining» more  KDD 2006»
16 years 2 months ago
Extracting key-substring-group features for text classification
In many text classification applications, it is appealing to take every document as a string of characters rather than a bag of words. Previous research studies in this area mostl...
Dell Zhang, Wee Sun Lee