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TJS
2010
182views more  TJS 2010»
14 years 8 months ago
A novel unsupervised classification approach for network anomaly detection by k-Means clustering and ID3 decision tree learning
This paper presents a novel host-based combinatorial method based on k-Means clustering and ID3 decision tree learning algorithms for unsupervised classification of anomalous and ...
Yasser Yasami, Saadat Pour Mozaffari
JIFS
2008
155views more  JIFS 2008»
14 years 10 months ago
Improving supervised learning performance by using fuzzy clustering method to select training data
The crucial issue in many classification applications is how to achieve the best possible classifier with a limited number of labeled data for training. Training data selection is ...
Donghai Guan, Weiwei Yuan, Young-Koo Lee, Andrey G...
NPL
2000
88views more  NPL 2000»
14 years 9 months ago
Learning Synaptic Clusters for Nonlinear Dendritic Processing
Nonlinear dendritic processing appears to be a feature of biological neurons and would also be of use in many applications of artificial neural networks. This paper presents a mod...
Michael W. Spratling, Gillian Hayes
ICASSP
2011
IEEE
14 years 1 months ago
Joint dictionary learning and topic modeling for image clustering
A new Bayesian model is proposed, integrating dictionary learning and topic modeling into a unified framework. The model is applied to cluster multiple images, and a subset of th...
Lingbo Li, Mingyuan Zhou, Eric Wang, Lawrence Cari...
SDM
2007
SIAM
176views Data Mining» more  SDM 2007»
14 years 11 months ago
Adaptive Concept Learning through Clustering and Aggregation of Relational Data
We introduce a new approach for Clustering and Aggregating Relational Data (CARD). We assume that data is available in a relational form, where we only have information about the ...
Hichem Frigui, Cheul Hwang