There are lots of R documents and over 3000 R packages. Which documents to start with and which R packages to use are questions faced by many people.

If you are new to R, an Introduction to R can be a good reference to start with, which is available at CRAN website. After that, you may want to know more details about R Language and data access, and they are documented respectively by the R Language Definition and R Data Import/Export at CRAN website.

More R Contributed Documents, including non-English ones are available at http://cran.r-project.org/other-docs.html. The R Journal is another source of documents on R techniques and packages.

If you prefer to learn R with examples, two excellent online resources are

- Quick-R, and

- R Tutorial.

If you want to use R for data mining, Data Mining with R – Learning by Case Studies is an excellent book to learn from.

Getting lost inĀ over 3000 R packages? Which R packages to use? CRAN Task Views are a good guidance. They provide collections of packages for different tasks. Some task views related to data mining are:

- CRAN Task View: Machine Learning & Statistical Learning,

- CRAN Task View: Cluster Analysis & Finite Mixture Models,

- CRAN Task View: Time Series Analysis,

- CRAN Task View: Multivariate Statistics, and

- CRAN Task View: Analysis of Spatial Data.

If you want to know which R functions and packages can be used for your data mining applications, R Reference Card for Data Mining will be helpful to you, which is available at RDataMining website <http://www.rdatamining.com>. Another useful document at the website is R and Data Mining: Example and Case Studies, which presents many examples on data mining with R.

Yanchang Zhao

RDataMining: http://www.rdatamining.com

Twitter: http://www.twitter.com/RDataMining

Group on Linkedin: http://group.rdatamining.com

Group on Google: http://group2.rdatamining.com

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