Statistical Data Mining

Statistical Data Mining

A text for a short course in statistical data mining.

Publication date: 01 May 2002

ISBN-10: n/a

ISBN-13: n/a

Paperback: 112 pages

Views: 3,202

Type: N/A

Publisher: n/a

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Post time: 13 Jun 2016 05:28:17

Statistical Data Mining

Statistical Data Mining A text for a short course in statistical data mining.
Tag(s): Data Mining Statistics
Publication date: 01 May 2002
ISBN-10: n/a
ISBN-13: n/a
Paperback: 112 pages
Views: 3,202
Document Type: N/A
Publisher: n/a
License: n/a
Post time: 13 Jun 2016 05:28:17
From the Preface:
Brian D. Ripley wrote:This is a short course in statistical data mining. As such we will not cover the aspects of data mining that are concerned with querying very large databases, although building efficient database interfaces to statistical software is becoming a very important area in statistical computing. Indeed, many of the problems arise with quite modest datasets with a thousand or so examples, but even those were not common a decade or two ago.

More course files are available here.




About The Author(s)


Brian Ripley was the Professor of Applied Statistics at the University of Oxford and a member of the Department of Statistics as well as a Professorial Fellow of St. Peter's College. He retired in August 2014 on grounds of ill health. Professor Ripley has made contributions to the fields of spatial statistics and pattern recognition. His work on artificial neural networks in the 1990s helped to bring aspects of machine learning and data mining to the attention of statistical audiences.

Brian D. Ripley

Brian Ripley was the Professor of Applied Statistics at the University of Oxford and a member of the Department of Statistics as well as a Professorial Fellow of St. Peter's College. He retired in August 2014 on grounds of ill health. Professor Ripley has made contributions to the fields of spatial statistics and pattern recognition. His work on artificial neural networks in the 1990s helped to bring aspects of machine learning and data mining to the attention of statistical audiences.


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