With the explosive growth in amount of information, it is highly required to utilize tools and methods in order to search, filter and manage resources. One of the major problems in text classification relates to the high dimensional feature spaces. Therefore, the main goal of text classification is to reduce the dimensionality of features space. There are many feature selection methods. However...

two different methods of bayesian segmentation algorithm were used with different band combinations. sequential maximum a posteriori (smap) is a bayesian image segmentation algorithm which unlike the traditional maximum likelihood (ml) classification attempts to improve accuracy by taking contextual information into account, rather than classifying pixels separately. landsat 7 etm+ data with pa...

in recent years, the needs of the internet are felt in lives of all people.  accordingly, many studies have been done on security in virtual environment. old technics such as firewalls, authentication and encryption could not provide internet security completely; so, intrusion detection system is created as a new solution and a defense wall in cyber environment. many studies were performed on d...

in this paper, we propose a new gene selection algorithm based on shuffled frog leaping algorithm that is called sfla-fs. the proposed algorithm is used for improving cancer classification accuracy. most of the biological datasets such as cancer datasets have a large number of genes and few samples. however, most of these genes are not usable in some tasks for example in cancer classification. ...

In this paper, a new hybrid methodology is introduced to design a cost-sensitive fuzzy rule-based classification system. A novel cost metric is proposed based on the combination of three different concepts: Entropy, Gini index and DKM criterion. In order to calculate the effective cost of patterns, a hybrid of fuzzy c-means clustering and particle swarm optimization algorithm is utilized. This ...

A new algorithm for classification of DMUs to efficient and inefficient units in data envelopment analysis is presented. This algorithm uses the non-Archimedean Charnes-Cooper-Rhodes[1] (CCR) model. Also, it applies an assurance value for the non-Archimedean                          using only simple computations on inputs and outputs of DMUs (see [18]). The convergence and efficiency of the ne...

in this paper, first, an initial feature vector for vocal fold pathology diagnosis is proposed. then, for optimizing the initial feature vector, a genetic algorithm is proposed. some experiments are carried out for evaluating and comparing the classification accuracies which are obtained by the use of the different classifiers (ensemble of decision tree, discriminant analysis and k-nearest neig...