DATA MINING Desktop Survival Guide by Graham Williams
Desktop Survival Project Home Preface List of Figures List of Tables Process . Data Graphics in R Understanding Data Preparing Data Building Models Evaluating Models Algorithms Apriori Bagging Bayes Classifier Boosting Conditional Trees Decision Trees Hierarchical Clustering Kernel Methods K-Means K-Nearest Neighbours Linear Models Logistic Regression Neural Networks Support Vector Machines Text Mining Open Products Borgelt Data Mining Suite R Rattle Weka Closed Products C4.5 Clementine Enterprise Miner Equbits Foresight GhostMiner InductionEngine ODM Statistica Data Miner TreeNet Virtual Predict Appendicies Glossary Bibliography Index

Summary

Market:	Statistical research.
Techniques:	Many are available as packages, including boosting (gbm), and random forests (randomForests).
Platforms:	Linux, Unix, MacOS, MSWindows.
Vendor:	The R Foundation for Statistical Computing.
Website:	http://www.r-project.org
Pricing:	Freely available -- GNU General Public License.

Brought to you by Togaware.