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» Mining Several Data Bases with an Ensemble of Classifiers
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IJSI
2008
156views more  IJSI 2008»
13 years 7 months ago
Co-Training by Committee: A Generalized Framework for Semi-Supervised Learning with Committees
Many data mining applications have a large amount of data but labeling data is often difficult, expensive, or time consuming, as it requires human experts for annotation. Semi-supe...
Mohamed Farouk Abdel Hady, Friedhelm Schwenker
GPEM
2010
134views more  GPEM 2010»
13 years 6 months ago
An ensemble-based evolutionary framework for coping with distributed intrusion detection
A distributed data mining algorithm to improve the detection accuracy when classifying malicious or unauthorized network activity is presented. The algorithm is based on genetic p...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...
BMCBI
2004
205views more  BMCBI 2004»
13 years 7 months ago
A combinational feature selection and ensemble neural network method for classification of gene expression data
Background: Microarray experiments are becoming a powerful tool for clinical diagnosis, as they have the potential to discover gene expression patterns that are characteristic for...
Bing Liu, Qinghua Cui, Tianzi Jiang, Songde Ma
SDM
2009
SIAM
162views Data Mining» more  SDM 2009»
14 years 4 months ago
Diversity-Based Weighting Schemes for Clustering Ensembles.
Clustering ensembles has been recently recognized as an emerging approach to provide more robust solutions to the data clustering problem. Current methods of clustering ensembles ...
Andrea Tagarelli, Francesco Gullo, Sergio Greco
ICPR
2010
IEEE
13 years 12 months ago
On-Line Fmri Data Classification Using Linear and Ensemble Classifiers
The advent of real-time fMRI pattern classification opens many avenues for interactive self-regulation where the brain's response is better modelled by multivariate, rather t...
Catrin Oliver Plumpton, Ludmila I. Kuncheva, David...