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—This paper describes a simulated annealing based multiobjective optimization algorithm that incorporates the concept of archive in order to provide a set of tradeoff solutions for the problem under consideration. To determine the acceptance probability of a new solution visa -vis the current solution, an elaborate procedure is followed that takes into(More)
In this paper, an evolutionary clustering technique is described that uses a new point symmetry-based distance measure. The algorithm is therefore able to detect both convex and non-convex clusters. Kd-tree based nearest neighbor search is used to reduce the complexity of finding the closest symmetric point. Adaptive mutation and crossover probabilities are(More)
In this paper, we propose classifier ensemble selection for Named Entity Recognition (NER) as a single objective optimization problem. Thereafter, we develop a method based on genetic algorithm (GA) to solve this problem. Our underlying assumption is that rather than searching for the best feature set for a particular classifier, ensembling of several(More)
— In this article, a new symmetry based genetic clustering algorithm is proposed which automatically evolves the number of clusters as well as the proper partitioning from a data set. Strings comprise both real numbers and the don't care symbol in order to encode a variable number of clusters. Here, assignment of points to different clusters are done based(More)
—In this paper, an automatic segmentation technique of multispectral magnetic resonance image of the brain using a new fuzzy point symmetry based genetic clustering technique is proposed. The proposed real-coded variable string length genetic fuzzy clustering technique (Fuzzy-VGAPS) is able to evolve the number of clusters present in the data set(More)
The entities mentioned in collections of scholarly articles in the Humanities (and in other scholarly domains) belong to different types from those familiar from news corpora, hence new resources need to be annotated to create supervised taggers for tasks such as ne extraction. However, in such domains there is a great need for making the best use possible(More)
In this paper a fuzzy point symmetry based genetic clustering technique (Fuzzy-VGAPS) is proposed which can determine the number of clusters present in a data set as well as a good fuzzy partitioning of the data. A new fuzzy cluster validity index, FSym-index, which is based on the newly developed point symmetry based distance is also proposed here.(More)