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JMLR
2010
116views more  JMLR 2010»
13 years 3 months ago
Feature Selection, Association Rules Network and Theory Building
As the size and dimensionality of data sets increase, the task of feature selection has become increasingly important. In this paper we demonstrate how association rules can be us...
Sanjay Chawla
ICDM
2009
IEEE
156views Data Mining» more  ICDM 2009»
13 years 6 months ago
Scalable Classification in Large Scale Spatiotemporal Domains Applied to Voltage-Sensitive Dye Imaging
We present an approach for learning models that obtain accurate classification of large scale data objects, collected in spatiotemporal domains. The model generation is structured ...
Igor Vainer, Sarit Kraus, Gal A. Kaminka, Hamutal ...
ICCV
2003
IEEE
14 years 10 months ago
A Sparse Probabilistic Learning Algorithm for Real-Time Tracking
This paper addresses the problem of applying powerful pattern recognition algorithms based on kernels to efficient visual tracking. Recently Avidan [1] has shown that object recog...
Oliver M. C. Williams, Andrew Blake, Roberto Cipol...
FLAIRS
2004
13 years 10 months ago
The Optimality of Naive Bayes
Naive Bayes is one of the most efficient and effective inductive learning algorithms for machine learning and data mining. Its competitive performance in classification is surpris...
Harry Zhang
CGF
2010
161views more  CGF 2010»
13 years 8 months ago
HyperMoVal: Interactive Visual Validation of Regression Models for Real-Time Simulation
During the development of car engines, regression models that are based on machine learning techniques are increasingly important for tasks which require a prediction of results i...
Harald Piringer, Wolfgang Berger, J. Krasser