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**: 4,049

**Type**: N/A

**Publisher**:
n/a

**License**:
n/a

**Post time**: 13 Jun 2016 05:28:17

Statistical Data Mining

A text for a short course in statistical data mining.

From the Preface:

More course files are available here.

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.

Tweet

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.

Book Categories

Computer Science
Introduction to Computer Science
Introduction to Computer Programming
Algorithms and Data Structures
Artificial Intelligence
Computer Vision
Machine Learning
Neural Networks
Game Development and Multimedia
Data Communication and Networks
Coding Theory
Computer Security
Information Security
Cryptography
Information Theory
Computer Organization and Architecture
Operating Systems
Image Processing
Parallel Computing
Concurrent Programming
Relational Database
Document-oriented Database
Data Mining
Big Data
Data Science
Digital Libraries
Compiler Design and Construction
Functional Programming
Logic Programming
Object Oriented Programming
Formal Methods
Software Engineering
Agile Software Development
Information Systems
Geographic Information System (GIS)

Mathematics
Mathematics
Algebra
Abstract Algebra
Linear Algebra
Number Theory
Numerical Methods
Precalculus
Calculus
Differential Equations
Category Theory
Proofs
Discrete Mathematics
Theory of Computation
Graph Theory
Real Analysis
Complex Analysis
Probability
Statistics
Game Theory
Queueing Theory
Operations Research
Computer Aided Mathematics

Supporting Fields
Web Design and Development
Mobile App Design and Development
System Administration
Cloud Computing
Electric Circuits
Embedded System
Signal Processing
Integration and Automation
Network Science
Project Management

Operating System
Programming/Scripting
Ada
Assembly
C / C++
Common Lisp
Forth
Java
JavaScript
Lua
Microsoft .NET
Rexx
Perl
PHP
Python
R
Rebol
Ruby
Scheme
Tcl/Tk

Miscellaneous
Sponsors