Pattern recognition systems are widely used in a host of different fields. Due to some reasons such as lack of knowledge about a method based on which the best classifier is detected for any arbitrary problem, and thanks to significant improvement in accuracy, researchers turn to ensemble methods in almost every task of pattern recognition. Classification as a major task in pattern recognition,...

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...

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...

Abstract Classifier chains are an effective technique for modeling label dependencies in multi-label classification. However, the method requires a fixed, static order of labels. While theory, any is sufficient, practice, this has substantial impact on quality final prediction. Dynamic classifier denote idea that each instance to classify, which labels predicted dynamically chosen. The complexi...

Abstract The Threshold-based Naïve Bayes (Tb-NB) classifier is introduced as a (simple) improved version of the original classifier. Tb-NB extracts sentiment from Natural Language text corpus and allows user not only to predict how much sentence positive (negative) but also quantify with numeric value. It based on estimation single threshold value that concurs define decision rule classifies in...

Objective(s): This study addresses feature selection for breast cancer diagnosis. The present process uses a wrapper approach using GA-based on feature selection and PS-classifier. The results of experiment show that the proposed model is comparable to the other models on Wisconsin breast cancer datasets. Materials and Methods: To evaluate effectiveness of proposed feature selection method, we ...