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2011•Applied Mechanics and MaterialsRequires access

Analysis and Improvement for K-Means Algorithm

Jing Xiao, Xiao Li

Open publisher page 1 citations

Abstract

K-Means algorithm is one of the mostly used foundation algorithm in data mining, it base on a greedy clustering algorithm. This paper will introduce this algorithm and analysis. Then prove the correctness of the algorithm. And then show the productivity of this algorithm. And at last, this paper will show some improvement to K-Means algorithm, including how to choose initial center points, and how to calculate the means. This will improve the algorithm at a certain extent.

About this research paper

What this paper is about

K-Means algorithm is one of the mostly used foundation algorithm in data mining, it base on a greedy clustering algorithm. This paper will introduce this algorithm and analysis. Then prove the correctness of the algorithm. And then show the productivity of this algorithm. And at last, this paper will show some improvement to K-Means algorithm, including how to choose initial center points, and how to calculate the means. This will improve the algorithm at a certain extent.

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OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Method / approach

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Available abstract

K-Means algorithm is one of the mostly used foundation algorithm in data mining, it base on a greedy clustering algorithm. This paper will introduce this algorithm and analysis. Then prove the correctness of the algorithm. And then show the productivity of this algorithm. And at last, this paper will show some improvement to K-Means algorithm, including how to choose initial center points, and how to calculate the means. This will improve the algorithm at a certain extent.

Key concepts: Correctness, Algorithm, Dinic's algorithm, Cluster analysis, Computer science, Greedy algorithm, Ramer–Douglas–Peucker algorithm, Base (topology)

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