In the last decades, a wide portfolio of Feature Weighting (FW) methods have been
proposed in the literature. Their main potential is the capability to transform the features in …

The massive growth of data in recent years has led challenges in data mining and machine
learning tasks. One of the major challenges is the selection of relevant features from the …

Abstract The Automatic Clustering using Differential Evolution (ACDE) is one of the grouping
methods capable of automatically determining the number of the cluster. However, ACDE …

Today's real-world data mostly involves incomplete, inconsistent, and/or irrelevant
information that causes many drawbacks to transform it into an understandable format. In …

Abstract Background and Objective The limited number of samples and high-dimensional
features in microarray data make selecting a small number of features for disease diagnosis …

Today's real-world data is frequently significant in size, with many redundant, missing, and
noise-based features and data instances must be addressed before applying various data …

Mean shift is a simple interactive procedure that gradually shifts data points towards the
mode which denotes the highest density of data points in the region. Mean shift algorithms …

This article focuses on determining the students´ interactions in the Virtual English Course
with Distance Education Model (DEM) at Mumbai University, in India. For this purpose, an …

In many practical applications, it is crucial to perform automatic data clustering without
knowing the number of clusters in advance. The evolutionary computation paradigm is good …

Despite being a well‐known problem, feature weighting and feature selection are a major
predicament for clustering. Most of the algorithms, which provide weighting or selection of …