text classification is an important research field in information retrieval and text mining. the main task in text classification is to assign text documents in predefined categories based on documents’ contents and labeled-training samples. since word detection is a difficult and time consuming task in persian language, bayesian text classifier is an appropriate approach to deal with different...

image classification is an issue which utilizes image processing, pattern recognition and classification methods. automatic medical image classification is a progressive area in image classification and it expected to be more developed in the future. due to this fact that automatic diagnosis which use intelligent methods such as medical image classification can assist pathologists by providing ...

Text Classification is an important research field in information retrieval and text mining. The main task in text classification is to assign text documents in predefined categories based on documents’ contents and labeled-training samples. Since word detection is a difficult and time consuming task in Persian language, Bayesian text classifier is an appropriate approach to deal with different...

Text Classification is an important research field in information retrieval and text mining. The main task in text classification is to assign text documents in predefined categories based on documents’ contents and labeled-training samples. Since word detection is a difficult and time consuming task in Persian language, Bayesian text classifier is an appropriate approach to deal with different...

In this paper, we evaluate and contrast two fuzzy classifiers for credit scoring. The first classifier uses evolutionary optimisation and boosting whereas the second classifier is based on a fuzzy neural network. We show that, for the case at hand, the boosted genetic fuzzy classifier performs better than both the neurofuzzy classifier and the well-known C4.5 algorithm that we included as a ref...

this paper is concerned with the development of a novel classifier for automatic mass detection of mammograms, based on contourlet feature extraction in conjunction with statistical and fuzzy classifiers. in this method, mammograms are segmented into regions of interest (roi) in order to extract features including geometrical and contourlet coefficients. the extracted features benefit from...

A new technique presents to improve the performance of dynamic voltage restorer (DVR) for voltage sag mitigation. This control scheme is based on cuckoo search algorithm with tree fuzzy rule based classifier (CSA-TFRC). CSA is used for optimizing the output of TFRC so the classification output of the network is enhanced. While, the combination of cuckoo search algorithm, fuzzy and decision tree...

This paper discusses a method for improving accuracy of fuzzy-rule-based classifiers using particle swarm optimization (PSO). Two different fuzzy classifiers are considered and optimized. The first classifier is based on Mamdani fuzzy inference system (M_PSO fuzzy classifier). The second classifier is based on TakagiSugeno fuzzy inference system (TS_PSO fuzzy classifier). The parameters of the ...