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DEXAW
2009
IEEE
173views Database» more  DEXAW 2009»
15 years 11 months ago
Automatic Cluster Number Selection Using a Split and Merge K-Means Approach
Abstract—The k-means method is a simple and fast clustering technique that exhibits the problem of specifying the optimal number of clusters preliminarily. We address the problem...
Markus Muhr, Michael Granitzer
ADMA
2006
Springer
172views Data Mining» more  ADMA 2006»
15 years 10 months ago
Experimental Comparison of Feature Subset Selection Using GA and ACO Algorithm
Abstract. Practical pattern classification and knowledge discovery problems require selecting a useful subset of features from a much larger set to represent the patterns to be cl...
Keunjoon Lee, Jinu Joo, Jihoon Yang, Vasant Honava...
GECCO
2005
Springer
113views Optimization» more  GECCO 2005»
15 years 10 months ago
Estimating the detector coverage in a negative selection algorithm
This paper proposes a statistical mechanism to analyze the detector coverage in a negative selection algorithm, namely a quantitative measurement of a detector set’s capability ...
Zhou Ji, Dipankar Dasgupta
DAGM
2004
Springer
15 years 10 months ago
Adaptive Feature Selection in Image Segmentation
Most image segmentation algorithms optimize some mathematical similarity criterion derived from several low-level image features. One possible way of combining different types of f...
Volker Roth, Tilman Lange
124
Voted
GECCO
2003
Springer
15 years 9 months ago
Selection Intensity in Asynchronous Cellular Evolutionary Algorithms
Abstract. This paper presents a theoretical study of the selection pressure in asynchronous cellular evolutionary algorithms (cEAs). This work is motivated by the search for a gene...
Mario Giacobini, Enrique Alba, Marco Tomassini