k-POD: A Method for k-Means Clustering of Missing Data
نویسندگان
چکیده
منابع مشابه
k-POD A Method for k-Means Clustering of Missing Data
The k-means algorithm is often used in clustering applications but its usage requires a complete data matrix. Missing data, however, is common in many applications. Mainstream approaches to clustering missing data reduce the missing data problem to a complete data formulation through either deletion or imputation but these solutions may incur significant costs. Our k-POD method presents a simpl...
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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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ژورنال
عنوان ژورنال: The American Statistician
سال: 2016
ISSN: 0003-1305,1537-2731
DOI: 10.1080/00031305.2015.1086685