On a correlational clustering of integers

TL;DR

This paper explores a novel correlation clustering method for integers using their greatest common divisor to minimize conflicts in the partitioning.

Contribution

It introduces a new correlation clustering approach specifically for integers based on their greatest common divisor, expanding the application of correlation clustering.

Findings

Developed a clustering method based on GCD

Analyzed conflict minimization in integer partitions

Provided theoretical insights into GCD-based clustering

Abstract

Correlation clustering is a concept of machine learning. The ultimate goal of such a clustering is to find a partition with minimal conflicts. In this paper we investigate a correlation clustering of integers, based upon the greatest common divisor.