MaxD K-Means: A clustering algorithm for auto-generation of centroids and distance of data points in clusters

• المؤلفون الرئيسيون: Wan Maseri, Wan Mohd, Beg, Abul Hashem, Herawan, Tutut, Fazley Rabbi, Khandakar
• التنسيق: مقال
• اللغة: English
• منشور في: Springer, Berlin, Heidelberg 2012
• الموضوعات: QA76 Computer software
• الوصول للمادة أونلاين: http://umpir.ump.edu.my/id/eprint/27004/1/MaxD%20K-Means-%20A%20clustering%20algorithm%20for%20auto-generation%20of%20centroids.pdf; http://umpir.ump.edu.my/id/eprint/27004/; https://doi.org/10.1007/978-3-642-34289-9_22; https://doi.org/10.1007/978-3-642-34289-9_22

K-Means is one of the unsupervised learning and partitioning clustering algorithms. It is very popular and widely used for its simplicity and fastness. The main drawback of this algorithm is that user should specify the number of cluster in advance. As an iterative clustering strategy, K-Means algor...