Classifiers based on bernoulli mixture models for text mining and handwriting recognition tasks

Proceedings of the International Joint Conference on Neural Networks

Volumn , Issue , 2008, Pages 2169-2175

  Saeed, Mehreen ^a   Babri, Haroon ^b  

^a NATIONAL UNIVERSITY OF COMPUTER AND EMERGING SCIENCES   (Pakistan)

^b UNIVERSITY OF ENGINEERING AND TECHNOLOGY   (Pakistan)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFIERS; DATA MINING; LEARNING SYSTEMS; MIXTURES; NEURAL NETWORKS;

ACCURACY RATES; BERNOULLI; BINARY DATUMS; BINARY FEATURES; CLASSIFICATION ACCURACIES; CLASSIFICATION ALGORITHMS; COMBINED MODELS; DATA SETS; DIMENSIONALITY REDUCTIONS; DO-MAINS; FEATURE SETS; HANDWRITING RECOGNITIONS; HYBRID MODELS; INPUT DATUMS; JOINT CONFERENCES; MIXTURE MODELS; PRIOR KNOWLEDGES; SAMPLE POINTS; TEXT MININGS;

FEATURE EXTRACTION;

EID: 56349115924     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2008.4634097     Document Type: Conference Paper

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