Comparison of K-Means and Fuzzy C-Means Algorithms on Different Cluster Structures

Cebeci, Zeynel and Yildiz, Figen (2015) Comparison of K-Means and Fuzzy C-Means Algorithms on Different Cluster Structures. AGRÁRINFORMATIKA / JOURNAL OF AGRICULTURAL INFORMATICS, 6 (3). pp. 13-23. ISSN 2061-862X

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Abstract

In this paper the K-means (KM) and the Fuzzy C-means (FCM) algorithmswere comparedfor their computing performance and clustering accuracyon different shaped cluster structures which are regularly and irregularly scatteredin two dimensional space. While the accuracyof the KM with single passwas lower than those of the FCM, the KM with multiple starts showed nearly the sameclustering accuracywith theFCM. Moreover the KMwith multiple startswas extremelysuperior to the FCM in computing timein all datasets analyzed. Therefore, when well separated cluster structures spreading with regular patterns do exist in datasets theKMwith multiple startswas recommended for cluster analysisbecause of its comparable accuracy and runtime performances.

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