<?xml version="1.0" encoding="utf-8" ?> <rss version="2.0" xmlns:opensearch="http://a9.com/-/spec/opensearch/1.1/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom"> <channel> <title> <![CDATA[CamTech Digital Library Search for 'au:&quot;Tibshirani, Robert.&quot;']]> </title> <!-- prettier-ignore-start --> <link> https://library.camtech.edu.kh/cgi-bin/koha/opac-search.pl?q=ccl=au%3A%22Tibshirani%2C%20Robert.%22&#38;sort_by=relevance&#38;format=rss </link> <!-- prettier-ignore-end --> <atom:link rel="self" type="application/rss+xml" href="https://library.camtech.edu.kh/cgi-bin/koha/opac-search.pl?q=ccl=au%3A%22Tibshirani%2C%20Robert.%22&#38;sort_by=relevance&#38;format=rss" /> <description> <![CDATA[ Search results for 'au:&quot;Tibshirani, Robert.&quot;' at CamTech Digital Library]]> </description> <opensearch:totalResults>3</opensearch:totalResults> <opensearch:startIndex>0</opensearch:startIndex> <opensearch:itemsPerPage>50</opensearch:itemsPerPage> <atom:link rel="search" type="application/opensearchdescription+xml" href="https://library.camtech.edu.kh/cgi-bin/koha/opac-search.pl?q=ccl=au%3A%22Tibshirani%2C%20Robert.%22&#38;sort_by=relevance&#38;format=opensearchdescription" /> <opensearch:Query role="request" searchTerms="q%3Dccl%3Dau%253A%2522Tibshirani%252C%2520Robert.%2522" startPage="" /> <item> <title> An introduction to statistical learning [electronic resource]: with applications in R / </title> <dc:identifier>ISBN:9781461471370 (acidfree paper) | 1461471370 (acidfree paper)</dc:identifier> <!-- prettier-ignore-start --> <link>https://library.camtech.edu.kh/cgi-bin/koha/opac-detail.pl?biblionumber=1213</link> <!-- prettier-ignore-end --> <description> <![CDATA[ <img src="https://images-na.ssl-images-amazon.com/images/P/1461471370.01.TZZZZZZZ.jpg" alt="" /> ]]> <![CDATA[ <p> .<br /> 1 digital resource (xvi, 426 pages) : , Includes index. 24 cm..<br /> 9781461471370 (acidfree paper) | 1461471370 (acidfree paper) </p> ]]> <![CDATA[ <p> <a href="https://library.camtech.edu.kh/cgi-bin/koha/opac-reserve.pl?biblionumber=1213">Place hold on <em>An introduction to statistical learning [electronic resource]:</em></a> </p> ]]> </description> <guid>https://library.camtech.edu.kh/cgi-bin/koha/opac-detail.pl?biblionumber=1213</guid> </item> <item> <title> The elements of statistical learning : data mining, inference, and prediction / </title> <dc:identifier>ISBN:9780387848570 | 9780387848587</dc:identifier> <!-- prettier-ignore-start --> <link>https://library.camtech.edu.kh/cgi-bin/koha/opac-detail.pl?biblionumber=2552</link> <!-- prettier-ignore-end --> <description> <![CDATA[ <img src="https://images-na.ssl-images-amazon.com/images/P/0387848576.01.TZZZZZZZ.jpg" alt="" /> ]]> <![CDATA[ <p> By Hastie, Trevor..<br /> New York, NY : Springer, 2009 .<br /> xxii, 745 p. : 25 cm..<br /> 9780387848570 | 9780387848587 </p> ]]> <![CDATA[ <p> <a href="https://library.camtech.edu.kh/cgi-bin/koha/opac-reserve.pl?biblionumber=2552">Place hold on <em>The elements of statistical learning :</em></a> </p> ]]> </description> <guid>https://library.camtech.edu.kh/cgi-bin/koha/opac-detail.pl?biblionumber=2552</guid> </item> <item> <title> The elements of statistical learning : data mining, inference, and prediction : with 200 full-color illustrations / </title> <dc:identifier>ISBN:0387952845 | 9780387952840</dc:identifier> <!-- prettier-ignore-start --> <link>https://library.camtech.edu.kh/cgi-bin/koha/opac-detail.pl?biblionumber=2597</link> <!-- prettier-ignore-end --> <description> <![CDATA[ <img src="https://images-na.ssl-images-amazon.com/images/P/0387952845.01.TZZZZZZZ.jpg" alt="" /> ]]> <![CDATA[ <p> By Hastie, Trevor..<br /> New York : Springer, 2001 .<br /> xvi, 745 p. : 25 cm..<br /> 0387952845 | 9780387952840 </p> ]]> <![CDATA[ <p> <a href="https://library.camtech.edu.kh/cgi-bin/koha/opac-reserve.pl?biblionumber=2597">Place hold on <em>The elements of statistical learning :</em></a> </p> ]]> </description> <guid>https://library.camtech.edu.kh/cgi-bin/koha/opac-detail.pl?biblionumber=2597</guid> </item> </channel> </rss>
