Comparison of the Accuracy of the Probabilistic Distance Clustering Method and Cluster Ensembles

Abstract

<jats:p>High accuracy of results is a very important aspect in any clustering problem t determines the effectiveness of decisions based on them. Therefore, literature proposes methods and solutions that aim to give more accurate and stable results than traditional clustering algorithms (e.g. k-means or hierarchical methods). Cluster ensembles (Leisch 1999; Dudoit, Fridlyand 2003; Hornik 2006; Fred, Jain 2002) or the distance clustering method (Ben-Israel, Iyigun 2008) are the examples of such solutions. Here, we carry out an experimental study to compare the accuracy of these two approaches.</jats:p>

Breast Cancer Detection Using Automated Segmentation and Genetic Algorithms

“…It implement the genetic algorithm using Galgo [ 23 ]. This software is an object-oriented programming (OOP) implementation in R. Further, it includes the code to develop models using Random Forest [ 28 , 45 ].…”