Isbn: 9781332247530 - using the kth nearest neighbor clustering procedure to determine the number of subpopulations (classic reprint) (3 risultati)

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  • Lingua: Inglese

    Editore: Forgotten Books, 2018

    1332247539 / 9781332247530

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    Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US

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    Condizione: Nuovo

    EUR 24,62

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    Spedito in U.S.A.

    Quantità: 15 disponibili

    PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

  • Lingua: Inglese

    Editore: Forgotten Books, 2018

    1332247539 / 9781332247530

    • Brossura

    Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK

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    Condizione: Nuovo

    EUR 24,29

    EUR 3,83 spedizione 
    Spedito da Regno Unito a U.S.A.

    Quantità: 15 disponibili

    PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

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    Lingua: Inglese

    Editore: Forgotten Books, 2018

    1332247539 / 9781332247530

    • Brossura
    • Print on Demand

    Da: Forgotten Books, London, Regno UnitoForgotten Books

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    Condizione: Nuovo

    EUR 15,68

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    Quantità: Più di 20 disponibili

    Paperback. Condizione: 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.…