Adaptive K-Means Clustering Techniques For Data Clustering
نویسندگان
چکیده
منابع مشابه
Adaptive K-Means Clustering
Clustering is used to organize data for efficient retrieval. One of the problems in clustering is the identification of clusters in given data. A popular technique for clustering is based on K-means such that the data is partitioned into K clusters. In this method, the number of clusters is predefined and the technique is highly dependent on the initial identification of elements that represent...
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Identifying clusters or clustering is an important aspect of data analysis. It is the task of grouping a set of objects in such a way those objects in the same group/cluster are more similar in some sense or another. It is a main task of exploratory data mining, and a common technique for statistical data analysis This paper proposed an improved version of K-Means algorithm, namely Persistent K...
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Thaddeus Tarpey and Eva Petkova 1 Department Mathematics and Statistics, Wright State University, Dayton, Ohio 45435, [email protected]. 2 Department of Child and Adolescent Psychiatry, New York University, New York, NY 10016-6023 Abstract Cluster analysis is a powerful tool for discovering sources of heterogeneity in data. However, clinically interesting sources of heterogeneity, such...
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ژورنال
عنوان ژورنال: International Journal of Innovative Research in Science, Engineering and Technology
سال: 2014
ISSN: 2319-8753
DOI: 10.15680/ijirset.2014.0309009