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TJS
2010
182views more  TJS 2010»
13 years 3 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»
13 years 11 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
13 years 11 months ago
Stability of k -Means Clustering
Shai Ben-David, Dávid Pál, Hans-Ulri...
PAMI
2002
243views more  PAMI 2002»
13 years 4 months ago
An Efficient k-Means Clustering Algorithm: Analysis and Implementation
Tapas Kanungo, David M. Mount, Nathan S. Netanyahu...
FOCS
2006
IEEE
13 years 11 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...