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...
Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Cambridge
Cambridge University Press
2024
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| Series: | Cambridge elements
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| Subjects: | |
| Online Access: | DE-12 DE-473 Volltext |
| 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 in this Element |
| Item Description: | Title from publisher's bibliographic system (viewed on 18 Dec 2024) |
| Physical Description: | 1 Online-Ressource (90 Seiten) |
| ISBN: | 9781009506625 |
| DOI: | 10.1017/9781009506625 |
Staff View
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Record in the Search Index
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| author | Argote, Denisse L. |
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| discipline | Geschichte Klassische Archäologie |
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| id | DE-604.BV050175681 |
| illustrated | Not Illustrated |
| indexdate | 2025-03-31T18:11:27Z |
| institution | BVB |
| isbn | 9781009506625 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-035511545 |
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| publishDate | 2024 |
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| publisher | Cambridge University Press |
| record_format | marc |
| series2 | Cambridge elements |
| spelling | Argote, Denisse L. Verfasser (DE-588)1359603220 aut Machine learning for archaeological applications in R Denisse L. Argote [and three others] Cambridge Cambridge University Press 2024 1 Online-Ressource (90 Seiten) txt rdacontent c rdamedia cr rdacarrier Cambridge elements Title from publisher's bibliographic system (viewed on 18 Dec 2024) 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 Archaeology / Data processing Machine learning R (Computer program language) Erscheint auch als Druck-Ausgabe 9781009506595 Erscheint auch als Druck-Ausgabe 9781009506649 https://doi.org/10.1017/9781009506625?locatt=mode:legacy Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Argote, Denisse L. Machine learning for archaeological applications in R Archaeology / Data processing Machine learning R (Computer program language) |
| title | Machine learning for archaeological applications in R |
| title_auth | Machine learning for archaeological applications in R |
| title_exact_search | Machine learning for archaeological applications in R |
| title_full | Machine learning for archaeological applications in R Denisse L. Argote [and three others] |
| title_fullStr | Machine learning for archaeological applications in R Denisse L. Argote [and three others] |
| title_full_unstemmed | Machine learning for archaeological applications in R Denisse L. Argote [and three others] |
| title_short | Machine learning for archaeological applications in R |
| title_sort | machine learning for archaeological applications in r |
| topic | Archaeology / Data processing Machine learning R (Computer program language) |
| topic_facet | Archaeology / Data processing Machine learning R (Computer program language) |
| url | https://doi.org/10.1017/9781009506625?locatt=mode:legacy |
| work_keys_str_mv | AT argotedenissel machinelearningforarchaeologicalapplicationsinr |