A novel feature selection and classification technique for face recognition is presented in this paper. Genetic Algorithms (GAs) for feature selection and Artificial Neural Network (ANN) for classification are incorporated in the proposed technique. The proposed GAs-ANN technique has two purposes in this research: 1) fusion and selection of features for face recognition. 2) location of signific...

This paper proposed a feature selection with privacy preservation in centralized network. Data can be preserved for privacy by perturbation technique as alias name. In centralized data evaluation, it makes data classification and feature selection for data mining decision model which make the structural information of model in this paper. The application of gain ratio technique for better perfo...

The work is concerned with the use of Ant Colony Optimization algorithm for feature selection of Keystrokes Dynamics and comparison of classification accuracy of Multi-SVM and KNN classifiers. There are various approaches used for feature subset selection but, ACO algorithm gives good performance than other feature selection algorithm like Genetic Based algorithm and Particle Swarm Optimization...

Text classification and feature selection plays an important role for correctly identifying the documents into particular category, due to the explosive growth of the textual information from the electronic digital documents as well as world wide web. In the text mining present challenge is to select important or relevant feature from large and vast amount of features in the data set. The aim o...

One of the main phases in the development of a system for the classiŽ cation of remote sensing images is the deŽ nition of an e€ ective set of features to be given as input to the classiŽ er. In particular, it is often useful to reduce the number of features available,while saving the possibility to discriminate among the di€ erent land-cover classes to be recognized. This paper addresses this ...

Last technological advances in wearable sensors and machine learning are allowing for a new generation of human monitoring techniques, especially devised for the analysis of biomechanics and activity patterns. In this paper, a novel technique to improve the identification of daily physical activity is presented. Taking into account the importance of data featuring and the selection of the most ...

In this paper we propose a novel approach for feature subset selection by the Polynomial Neural Network (PNN) using Genetic Algorithm (GA). A randomly selected subset of features of a d ataset is passed to the PNN as input. The classification accuracy of PNN is taken as the fitness function of GA. In the conventional PNN approaches, published in literature so far, the processing by PNN takes la...

The Classification are carried out using various feature selection technique. The feature selection methods allows the classification to be carried out more accurately and efficiently. Feature selection is one of the leading trends in the research work going on. There are various feature selection methods which are used along with the classification methods. According to the application the mos...

Feature subset selection (FSS) is a known technique to pre-process the data before performing any data mining tasks, e.g., classification and clustering. FSS provides both cost-effective predictors and a better understanding of the underlying process that generated data. We propose Corona, a simple yet effective supervised feature subset selection technique for Multivariate Time Series (MTS). T...

Remote sensing research focusing on feature selection has long attracted the attention of the remote sensing community because feature selection is a prerequisite for image processing and various applications. Different feature selection methods have been proposed to improve the classification accuracy. They vary from basic search techniques to clonal selections, and various optimal criteria ha...