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» Learn .MF: A random subspace approach for the missing featu...
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PR
2010
99views more  PR 2010»
13 years 3 months ago
Learn++.MF: A random subspace approach for the missing feature problem
Robi Polikar, Joseph DePasquale, Hussein Syed Moha...
IJCNN
2007
IEEE
13 years 11 months ago
Random Feature Subset Selection for Analysis of Data with Missing Features
Abstract - We discuss an ensemble-of-classifiers based algorithm for the missing feature problem. The proposed approach is inspired in part by the random subspace method, and in pa...
Joseph DePasquale, Robi Polikar
JMLR
2008
168views more  JMLR 2008»
13 years 4 months ago
Max-margin Classification of Data with Absent Features
We consider the problem of learning classifiers in structured domains, where some objects have a subset of features that are inherently absent due to complex relationships between...
Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbe...
KDD
2007
ACM
190views Data Mining» more  KDD 2007»
14 years 5 months ago
Model-shared subspace boosting for multi-label classification
Typical approaches to multi-label classification problem require learning an independent classifier for every label from all the examples and features. This can become a computati...
Rong Yan, Jelena Tesic, John R. Smith
IJCV
2006
206views more  IJCV 2006»
13 years 4 months ago
Random Sampling for Subspace Face Recognition
Subspacefacerecognitionoftensuffersfromtwoproblems:(1)thetrainingsamplesetissmallcompared with the high dimensional feature vector; (2) the performance is sensitive to the subspace...
Xiaogang Wang, Xiaoou Tang