Machine Learning for Archaeological Applications in R
Seiten
2024
Cambridge University Press (Verlag)
978-1-009-50659-5 (ISBN)
Cambridge University Press (Verlag)
978-1-009-50659-5 (ISBN)
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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. It also provides a detailed explanation of how to process data in R as well as the respective code.
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.
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.
1. Introduction; 2. Processing spectral data; 3. Processing compositional data; 4. Processing a combination of spectral and compositional data; 5. Final comments; Abbreviations; References.
| Erscheinungsdatum | 22.08.2024 |
|---|---|
| Reihe/Serie | Elements in Current Archaeological Tools and Techniques |
| Zusatzinfo | Worked examples or Exercises |
| Verlagsort | Cambridge |
| Sprache | englisch |
| Themenwelt | Geisteswissenschaften ► Archäologie |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Mathematik / Informatik ► Mathematik ► Statistik | |
| ISBN-10 | 1-009-50659-5 / 1009506595 |
| ISBN-13 | 978-1-009-50659-5 / 9781009506595 |
| Zustand | Neuware |
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