An efficientk-means-type algorithm for clustering datasets with incomplete records

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An efficient k-means-type algorithm for clustering datasets with incomplete records

The k-means algorithm is the most popular nonparametric clustering method in use, but cannot generally be applied to data sets with missing observations. The usual practice with such data sets is to either impute the values under an assumption of a missing-at-random mechanism or to ignore the incomplete records, and then to use the desired clustering method. We develop an efficient version of t...

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ژورنال

عنوان ژورنال: Statistical Analysis and Data Mining: The ASA Data Science Journal

سال: 2018

ISSN: 1932-1864

DOI: 10.1002/sam.11392