Data Mining and R

October 24, 2009

(This article was first published on Jeromy Anglim's Blog: Psychology and Statistics, and kindly contributed to R-bloggers)

This post lists a few data mining resources in R. I also provide a few observations on the distinction between data mining, data analysis, and statistics as it pertains to the analysis work that I do in psychology.

Online Resources

The classic book The Elements of Statistical Learning by Hastie, Tibshirani, Friedman is available for free online. There’s also an accompanying R package.
I previously discussed David Mease’s online data mining course
Rattle – a data mining GUI for R.
Some comments on data mining by John Maindonald
Luis Torgo has a book currently available online providing demonstrations of data mining using R
Cran Task View on Machine Learning & Statistical Learning

Some Casual Observations

Data mining seems more concerned with prediction using observed variables than with understanding the causal system of latent variables; psychology is typically more concerned with the causal system of latent variables.
Data mining typically involves massive datasets (e.g. 10,000 + rows) collected for a purpose other than the purpose of the data mining. Psychological datasets are typically small (e.g., less than 1,000 or 100 rows) and collected explicitly to explore a research question.
Psychological analysis typically involves testing specific models. Automated model development approaches tend not to be theoretically interesting.