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TJS
2010
182views more  TJS 2010»
13 years 5 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
ISAAC
2009
Springer
175views Algorithms» more  ISAAC 2009»
14 years 1 months ago
Worst-Case and Smoothed Analysis of k-Means Clustering with Bregman Divergences
The k-means algorithm is the method of choice for clustering large-scale data sets and it performs exceedingly well in practice. Most of the theoretical work is restricted to the c...
Bodo Manthey, Heiko Röglin
COLT
2007
Springer
14 years 1 months ago
Stability of k -Means Clustering
Shai Ben-David, Dávid Pál, Hans-Ulri...
PAMI
2002
243views more  PAMI 2002»
13 years 6 months ago
An Efficient k-Means Clustering Algorithm: Analysis and Implementation
Tapas Kanungo, David M. Mount, Nathan S. Netanyahu...
FOCS
2006
IEEE
14 years 1 months ago
The Effectiveness of Lloyd-Type Methods for the k-Means Problem
We investigate variants of Lloyd’s heuristic for clustering high dimensional data in an attempt to explain its popular
Rafail Ostrovsky, Yuval Rabani, Leonard J. Schulma...