Machine learning for archaeological applications in R /
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 t...
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| Format: | Book |
| Language: | English |
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Cambridge ; New York :
Cambridge University Press,
2024.
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| Series: | Cambridge elements. Elements in current archaeological tools and techniques.
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| Subjects: |
| Summary: | 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. |
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| Physical Description: | 90 pages : illustrations ; 24 cm. |
| Bibliography: | Includes bibliographical references (pages [84]-90). |
| ISBN: | 1009506595 9781009506595 1009506641 9781009506649 |