A k-means algorithm is a method for clustering that has already gained a wide range of
acceptability. However, its performance extremely depends on the opening cluster centers …

Data clustering is an important technique of data mining in which the objective is to partition
N data objects into K clusters that minimize the sum of intra‐cluster distances between each …

Data clustering is a prevalent problem that belongs to the data mining domain. It aims to
partition the given data objects into some specified number of clusters based on the sum of …

Data clustering is a crucial machine learning technique that helps divide a given dataset into
many similar data objects where the data members resemble each other. It is an …

Multiobjective optimization problems (MOPs) are very popular these days and have gained
continuous research attention. These problems involve a minimum of two conflicting …

Clustering plays a crucial role in data mining and machine learning, with the primary
objective being the identification of cohesive and distinct data groups, enabling the …