Feature Selection Methods Based on Symmetric Uncertainty Coefficients and Independent Classification Information

A New Hybrid Framework for Filter based Feature Selection using Information Gain and Symmetric Uncertainty (TECHNICAL NOTE)

Feature selection is a pre-processing technique used for eliminating the irrelevant and redundant features which results in enhancing the performance of the classifiers. When a dataset contains more irrelevant and redundant features, it fails to increase the accuracy and also reduces the performance of the classifiers. To avoid them, this paper presents a new hybrid feature selection method usi...

A Real-Time Electroencephalography Classification in Emotion Assessment Based on Synthetic Statistical-Frequency Feature Extraction and Feature Selection

Purpose: To assess three main emotions (happy, sad and calm) by various classifiers, using appropriate feature extraction and feature selection. Materials and Methods: In this study a combination of Power Spectral Density and a series of statistical features are proposed as statistical-frequency features. Next, a feature selection method from pattern recognition (PR) Tools is presented to e...

Feature Selection for Plant Leaf Classification Based on Information Gain

Feature selection methods have been explored in the literature for the classification techniques, among which correlated feature, information gain, mutual information and chi-square are considered more effective. The leaf images contain inherent noise due to imaging equipment, operating environment and position of the image during image acquisition. In this paper, a method for classification of...

Feature Selection Using Classification Methods

Theoretical evaluation of feature selection methods based on mutual information

Feature selection methods are usually evaluated by wrapping specific classifiers and datasets in the evaluation process, resulting very often in unfair comparisons between methods. In this work, we develop a theoretical framework that allows obtaining the true feature ordering of two-dimensional sequential forward feature selection methods based on mutual information, which is independent of en...