DATA MINING Desktop Survival Guide by Graham Williams
Desktop Survival Project Home List of Figures List of Tables Data Mining Data Mining Data Mining with Rattle Introduction Data Transform Explore A Model Building Framework Unsupervised Modelling Two Class Models Multi Class Models Regression Models Text Mining Evaluation and Deployment Moving into R Troubleshooting R for the Data Miner R Data Graphics in R Understanding Data Preparing Data Building Models Evaluating Models Algorithms Apriori Bagging Bayes Classifier Boosting Cluster Analysis Conditional Trees Hierarchical Clustering K-Means K-Nearest Neighbours Linear Models Logistic Regression Neural Networks Support Vector Machines Text Mining Open Products AlphaMiner Borgelt Data Mining Suite KNime R Rattle Weka Closed Products C4.5 Clementine Equbits Foresight GhostMiner InductionEngine ODM Enterprise Miner Statistica Data Miner TreeNet Virtual Predict Appendicies Glossary Bibliography Index

Further Resources

Useful on-line statistical resources include:

• http://wikipedia.org/Wikipedia has a growing collection of statistical entries.
• http://www.itl.nist.gov/div898/handbook/index.htmNIST
• http://www.statsoftinc.com/textbook/stathome.htmlStatSoft
• http://www.tufts.edu/ gdallal/LHSP.HTMTufts
• http://addictedtor.free.fr/graphiques/R Graph Gallery

Support further development through the purchase of the PDF version of the book.
Brought to you by Togaware.