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...
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...
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 ...
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...
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...