Analysis of K-Means Algorithm

Download Now
Provided by: IJAIR
Topic: Data Management
Format: PDF
Clustering performance of the K-means greatly relies upon the correctness of the initial centroids. Usually the initial centroids for the K-means clustering are determined randomly so that the determined centroids may reach the nearest local minima, not the global optimum. This paper proposes a new approach to optimizing the designation of initial centroids for K-means clustering. This approach is inspired by the thought process of determining a set of pillars' locations in order to make a stable house or building.
Download Now

Find By Topic