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Using the Kth Nearest Neighbor Clustering Procedure to Determine the Number of Subpopulations (Classic Reprint) - Softcover

 
9781332247530: Using the Kth Nearest Neighbor Clustering Procedure to Determine the Number of Subpopulations (Classic Reprint)

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Excerpt from Using the Kth Nearest Neighbor Clustering Procedure to Determine the Number of Subpopulations

The problem of hypothesis testing under the density-contour cluster ing model did not receive much attention. (see however, Hartigan (1977)

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This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.

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  • PublisherForgotten Books
  • Publication date2018
  • ISBN 10 1332247539
  • ISBN 13 9781332247530
  • BindingPaperback
  • LanguageEnglish
  • Number of pages42

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M. Anthony Wong, Christian Schaak
Published by Forgotten Books, 2018
ISBN 10: 1332247539 ISBN 13: 9781332247530
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Paperback. Condition: New. Print on Demand. This book introduces the kth nearest neighbor clustering procedure, a groundbreaking advancement in cluster analysis, the science of organizing data by similarities to discover patterns. The kth nearest neighbor clustering procedure is a powerful tool for detecting subpopulations within data, offering a robust and consistent approach to cluster identification. The author explores the theoretical foundations and practical applications of the kth nearest neighbor clustering procedure, providing a thorough understanding of its advantages and limitations. With a focus on its ability to identify modes within a population's density function, the book demonstrates how this procedure can uncover hidden structures within data. The author also delves into the statistical aspects of cluster analysis, discussing hypothesis testing and significance levels. The kth nearest neighbor clustering procedure is presented as an innovative tool for assessing the number of subpopulations present in a dataset, making it useful for researchers across various disciplines seeking to understand the underlying structure of their data. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item. Seller Inventory # 9781332247530_0

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ISBN 10: 1332247539 ISBN 13: 9781332247530
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M. Anthony Wong
Published by Forgotten Books, 2018
ISBN 10: 1332247539 ISBN 13: 9781332247530
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