Feature selection aims to choose an optimal subset of features that are necessary and sufficient to improve the generalization performance and the running efficiency of the learning algorithm. To get the optimal subset in the feature selection process, a hybrid feature selection based on mutual information and genetic algorithm is proposed in this paper. In order to make full use of the advanta...

Using the rapid growth of computational biology and e-commerce applications, high-dimensional data becomes usual. Thus, mining high dimensional data is an urgent problem of great practical importance. Within the high dimensional data the dimensional reduction is a vital factor, to the purpose the clustering based feature subset selection algorithm is proposed in this particular paper. The chara...

In this paper, we examine a method for feature subset selection based on Information Theory. Initially, a framework for de ning the theoretically optimal, but computationally intractable, method for feature subset selection is presented. We show that our goal should be to eliminate a feature if it gives us little or no additional information beyond that subsumed by the remaining features. In pa...

Accurate recognition of person identity is a critical task in civil society for various application and different needs. There are well-established biometric modalities that can be used purposes such as face, voice, fingerprint, iris, etc. Recently, face images have been widely recognition, since the human most natural user-friendly method. However, real-life applications, some factors may degr...

Real world data sets usually have many features, which increases the complexity of data mining task. Feature selection, as a preprocessing step to the data mining, has been shown very effective in reducing dimensionality, removing irrelevant data, increasing learning accuracy, and improving comprehensibility. To find the optimal feature subsets is the aim of feature selection. Rough sets theory...

Background: In the current study, a hybrid feature selection approach involving filter and wrapper methods is applied to some bioscience databases with various records, attributes and classes; hence, this strategy enjoys the advantages of both methods such as fast execution, generality, and accuracy. The purpose is diagnosing of the disease status and estimating of the patient survival. Method...