Feature selection is the process of selecting a subset of optimal features by removing
redundant and irrelevant features. In supervised learning, feature selection process uses …

Feature selection is selecting a subset of optimal features. Feature selection is being used in
high dimensional data reduction and it is being used in several applications like medical …

Prediction plays a vital role in decision making. Correct prediction leads to right decision
making to save the life, energy, efforts, money and time. The right decision prevents physical …

Feature selection, both for supervised as well as for unsupervised classification is a relevant
problem pursued by researchers for decades. There are multiple benchmark algorithms …

Feature selection is the process of eliminating features from the data set that are irrelevant
with respect to the task to be performed. Feature selection is important for many reasons …

In this article, we propose an unsupervised feature selection algorithm based on the recently
developed shrinking and expansion algorithm (SEA). The SEA is already an established …

Feature selection is a fundamental preprocess before performing actual learning; especially
in unsupervised manner where the data are unlabeled. Essentially, when there are too …

Metaheuristic algorithms are basically used to explore search space to find optimal
solutions. It is a form of generalized local search which gives a good solution for optimization …

In recent years, Jaya optimization algorithm has been successfully applied in several
optimization problems. This paper presents a novel feature selection (FS) approach based …

One way to improve accuracy of a classifier is to use the minimum number of features. Many
feature selection techniques are proposed to find out the most important features. In this …