Factors Affecting Efficiency of K-means Algorithm
Sonal Miglani, Kanwal Garg · 2013
K-means algorithm is a simple technique that partitions a dataset into groups of sensible patterns. It is well known for clustering large datasets and generating effective results that are used in a variety of scientific applications such as Data Mining, knowledge discovery, data compression, vector quantization and medical imaging. The performance of this algorithm can be improved further by studying all those factors that plays a crucial role in its functionality. The aim of this research paper is to uncover the significant factors in order to enhance the efficiency as well as reducing the complexity of K-means algorithm.