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KBS
2008
98views more  KBS 2008»
13 years 3 months ago
Mixed feature selection based on granulation and approximation
Feature subset selection presents a common challenge for the applications where data with tens or hundreds of features are available. Existing feature selection algorithms are mai...
Qinghua Hu, Jinfu Liu, Daren Yu
CVPR
2010
IEEE
13 years 4 months ago
High performance object detection by collaborative learning of Joint Ranking of Granules features
Object detection remains an important but challenging task in computer vision. We present a method that combines high accuracy with high efficiency. We adopt simplified forms of...
Chang Huang, Ramakant Nevatia
ICMLA
2008
13 years 6 months ago
Highly Scalable SVM Modeling with Random Granulation for Spam Sender Detection
Spam sender detection based on email subject data is a complex large-scale text mining task. The dataset consists of email subject lines and the corresponding IP address of the em...
Yuchun Tang, Yuanchen He, Sven Krasser
ASIAMS
2007
IEEE
13 years 11 months ago
Rough-Fuzzy Granulation, Rough Entropy and Image Segmentation
This talk has two parts explaining the significance of Rough sets in granular computing in terms of rough set rules and in uncertainty handling in terms of lower and upper approxi...
Sankar K. Pal
BMCBI
2010
178views more  BMCBI 2010»
13 years 4 months ago
Selecting high-dimensional mixed graphical models using minimal AIC or BIC forests
Background: Chow and Liu showed that the maximum likelihood tree for multivariate discrete distributions may be found using a maximum weight spanning tree algorithm, for example K...
David Edwards, Gabriel C. G. de Abreu, Rodrigo Lab...