{"product_id":"machine-learning-for-archaeological-applications-in-r-hardback-9781009506595","title":"Machine Learning for Archaeological Applications in R (Hardback) 9781009506595","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eMachine Learning for Archaeological Applications in R\u003c\/font\u003e\u003cbr\u003e\r\n\r\n\r\n\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003eThis Element highlights the employment within archaeology of classification methods in chemometrics, AI, and Bayesian statistics.\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003eDenisse L. Argote (Author), Pedro A. López-­García (Author), Manuel A. Torres-­García (Author), Michael C. Thrun (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781009506595, Cambridge University Press\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 16 January 2025\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e96 pages\u003cbr\u003e22.9 x 15.2 x 0.6 cm, 0.281 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003eThis 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.\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e1. Introduction\u003cbr\u003e 2. Processing spectral data\u003cbr\u003e 3. Processing compositional data\u003cbr\u003e 4. Processing a combination of spectral and compositional data\u003cbr\u003e 5. Final comments\u003cbr\u003e Abbreviations\u003cbr\u003e References.\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Archaeology [\u003ca title=\"See our other books on Archaeology\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Archaeology%20%5BHD%5D%22\"\u003eHD\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Cambridge University Press","offers":[{"title":"Brand New","offer_id":52415623561496,"sku":"9781009506595","price":49.79,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9781009506595i.jpg?v=1784419300","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/machine-learning-for-archaeological-applications-in-r-hardback-9781009506595","provider":"Freshly Printed Books","version":"1.0","type":"link"}