in this paper, an unsupervised classification method using spatial contextual information for polarimetric sar (polsar) image classification is proposed. first, an unsupervised classification based on 2d h/▁α plane was performed, using cloude/pottier target decomposition algorithm. in order to compute the initial values of the cluster centers and hence a rapid convergence of the algorithm, the ...

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this paper considers the generation of some interpretable fuzzy rules for assigning an amino acid sequence into the appropriate protein superfamily. since the main objective of this classifier is the interpretability of rules, we have used the distribution of amino acids in the sequences of proteins as features. these features are the occurrence probabilities of six exchange groups in the seque...

Abdul Qadir Jurjânî, with his two famous books, is the most important scholar of Islamic rhetoric. He is the founder of rhetoric in the Muslim world. One of Jurjânî’s most prominent accomplishments is his comprehensive classification of metaphors. First of all, Jurjânî distinguishes between non-expressive and expressive metaphors, and then presents subclasses for expressive, or “useful”, metaph...

Nowadays, marketing serves the purpose of maximizing customer lifetime value (CLV) and customer equity, which is the sum of the lifetime values of the company’s customers. But, CLV calculation encounters some difficulties which limit the usage of this technique. Nonetheless, companies looking for methods to know how to calculate their customers’ CLV. In this paper, fuzzy classification rules we...

  Among various statistical and data mining discriminant analysis proposed so far for group classification, linear programming discriminant analysis has recently attracted the researchers’ interest. This study evaluates multi-group discriminant linear programming (MDLP) for classification problems against well-known methods such as neural networks and support vector machine. MDLP is less compli...

Discriminant analysis is a classification method that can predict the group membership of a newly sampled observation. In discriminant analysis, classification of new observed data has an uncertainty. In this paper, the confidence degree is introduced to determine the confidence of classification of new observed data. Then, a Monte Carlo-based sensitivity analysis is applied to an assessment of...