Table of Contents
- Setting GNU R for predictive modeling
- Basic data visualization with tools built-in in R
- Data visualization with lattice
- Unsupervized learning: clustering with k-means
- Unsupervized learning: Hierarchical clustering
- Unsupervized learning: Principal Component Analysis
- Unsupervized learning: market basket analyses with Apriori (association rules)
- Probability Distributions, Covariance, and Correlation
- Regression
- Classification with na
- Decision trees
- Multilevel regression in R
- Text Analytics with R
- PMML
- Appendix, Solution to exercises
- References

