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Complete Gradient Clustering Algorithm for Features Analysis of X-Ray Images
Methods based on kernel density estimation have been successfully applied for various data mining tasks. Their natural interpretation together with suitable properties make them an attractive toolExpand
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Clustering using flower pollination algorithm and Calinski-Harabasz index
Task of clustering, that is data division into homogeneous groups represents one of the elementary problems of contemporary data mining. Cluster analysis can be approached through variety of methodsExpand
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Study of Flower Pollination Algorithm for Continuous Optimization
Modern optimization has in its disposal an immense variety of heuristic algorithms which can effectively deal with both continuous and combinatorial optimization problems. Recent years brought inExpand
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Therapeutic effects of imipramine are counteracted by its metabolite, desipramine, in patients with generalized anxiety disorder.
Imipramine has been shown to reduce anxiety in patients with generalized anxiety disorder (GAD). However, some properties of imipramine may diminish or counteract its anxiolytic effects. The authorsExpand
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Sensitivity Analysis for Probabilistic Neural Network Structure Reduction
In this paper, we propose the use of local sensitivity analysis (LSA) for the structure simplification of the probabilistic neural network (PNN). Three algorithms are introduced. The first algorithmExpand
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Weighted probabilistic neural network
Abstract In this work, the modification of the probabilistic neural network (PNN) is proposed. The traditional network is adjusted by introducing the weight coefficients between pattern and summationExpand
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Fully informed swarm optimization algorithms: Basic concepts, variants and experimental evaluation
Particle swarm optimization constitutes currently one of the most important nature-inspired metaheuristics, used successfully for both combinatorial and continuous problems. Its popularity hasExpand
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A Complete Algorithm for the Reduction of Pattern Data in the Classification of Interval Information
The aim of this paper is to present a novel method of data sample reduction that can be applied, in particular, to the classification of interval type imprecise information. Its concept is based onExpand
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The Complete Gradient Clustering Algorithm: properties in practical applications
The aim of this paper is to present a Complete Gradient Clustering Algorithm, its applicational aspects and properties, as well as to illustrate them with specific practical problems from the subjectExpand
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