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

Data Mining
With Rattle and R

Open Source Desktop Survival Guide

Graham Williams

http://togaware.com

The procedures and applications presented in this book have been included for their instructional value. They have been tested but are not guaranteed for any particular purpose. Neither the publisher nor the author offer any warranties or representations, nor do they accept any liabilities with respect to the programs and applications.

The book, as you see it presently, is a work in progress, and different sections are progressed depending on feedback. Please send comments, suggestions, updates, and criticisms to Graham.Williams@togaware.com.

I hope you find it useful!

Printed March 9, 2007  

Copyright © 2006-2007 by Graham Williams

ISBN 0-9757109-2-3

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