Feature Selection Library (FSLib) is a widely applicable MATLAB library for Feature Selection (FS). FS is an essential component of machine learning and data mining which has been studied for many years under many different conditions and in diverse scenarios. These algorithms aim at ranking and selecting a subset of relevant features according to their degrees of relevance, preference, or importance as defined in a specific application. Because feature selection can reduce the amount of features used for training classification models, it alleviates the effect of the curse of dimensionality, speeds up the learning process, improves model's performance, and enhances data understanding. This short report provides an overview of the feature selection algorithms included in the FSLib MATLAB toolbox among filter, embedded, and wrappers methods.
翻译:功能选择图书馆(FSLib)是一个广泛应用的 MATLAB 功能选择图书馆(FS) 。 FS 是机器学习和数据挖掘的基本组成部分,多年来在许多不同条件下和不同情景下进行了研究,这些算法旨在根据具体应用中界定的相关程度、偏好程度或重要性,对相关特征进行分级和选择。由于特性选择可以减少培训分类模型所使用的特征数量,因此可以减轻维度诅咒的影响,加快学习过程,改进模型的性能,提高数据理解度。这份简短报告概述了FSLib MATLAB工具箱中包含的过滤、嵌入和包装方法的特征选择算法。