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 …

Feature selection (FS) methods can be used in data pre-processing to achieve efficient data
reduction. This is useful for finding accurate data models. Since exhaustive search for …

Abstract In Machine Learning (ML), Feature Selection (FS) plays a crucial part in reducing
data's dimensionality and enhancing any proposed framework's performance. However, in …

A new correlation-based filter approach for simple, fast, and effective feature selection (FS)
is proposed. The association strength between each feature and the response variable …

With the current trend of rapidly growing popularity of the Python programming language for
machine learning applications, the gap between machine learning engineer needs and …

Feature selection aims at selecting important features that can enhance learning
performance in data mining, pattern recognition, and machine learning. Filter feature …

Feature selection (FS) is an important research topic in the area of data mining and machine
learning. FS aims at dealing with the high dimensionality problem. It is the process of …

The Feature Selection problem involves discovering a subset of features, such that a
classifier built only with this subset would have better predictive accuracy than a classifier …

In this paper, we examine the advantages and disadvantages of filter and wrapper methods
for feature selection and propose a new hybrid algorithm that uses boosting and …

Feature selection (FS), sometimes called variable selection, is an important preprocessing
step for several data mining applications. FS is characterized by the process of selecting …