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Machine Learning for Archaeological Applications in R

Machine Learning for Archaeological Applications in R

Machine Learning for Archaeological Applications in R

Denisse L. Argote, Instituto Nacional de Antropología e Historia
Pedro A. López-­García, Escuela Nacional de Antropología e Historia
Manuel A. Torres-­García, Instituto Nacional de Antropología e Historia
Michael C. Thrun, Philipps-Universität Marburg, Germany
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9781009506618

    This Element highlights the employment within archaeology of classification methods developed in the field of chemometrics, artificial intelligence, and Bayesian statistics. These run in both high- and low-dimensional environments and often have better results than traditional methods. Instead of a theoretical approach, it provides examples of how to apply these methods to real data using lithic and ceramic archaeological materials as case studies. A detailed explanation of how to process data in R (The R Project for Statistical Computing), as well as the respective code, are also provided in this Element.

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    No date available
    Adobe eBook Reader
    9781009506618
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    Table of Contents

    • 1. Introduction
    • 2. Processing spectral data
    • 3. Processing compositional data
    • 4. Processing a combination of spectral and compositional data
    • 5. Final comments
    • Abbreviations
    • References.
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      Authors
    • Denisse L. Argote , Instituto Nacional de Antropología e Historia
    • Pedro A. López-­García , Escuela Nacional de Antropología e Historia
    • Manuel A. Torres-­García , Instituto Nacional de Antropología e Historia
    • Michael C. Thrun , Philipps-Universität Marburg, Germany