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Machine Learning for Archaeological Applications in R

Argote, Denisse L.

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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.

Accessories:

No Accessory

Publisher

CAMBRIDGE

Bisac Major Subject

Social Science

Bisac Minor Subject

Archaeology

Binding Type

Hardcover

Country Of Origin

Number Of Units

Length

9.0 Inches

Barcode Indicator

EAN

Width

6.0 Inches

Publication Date

1970-01-01

Height

0.25 Inches

ISBN 10

1009506595

Weight

0.67 Pounds

Book EAN

9781009506595

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Machine Learning for Archaeological Applications in R