DATA MINING Desktop Survival Guide by Graham Williams
Desktop Survival Project Home Preface List of Figures List of Tables Enterprise Data Mining Process Rattle Data Explore R Data Graphics in R Understanding Data Preparing Data Building Models Evaluating Models Algorithms Apriori Bagging Bayes Classifier Boosting Conditional Trees Hierarchical Clustering K-Means K-Nearest Neighbours 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

The Process

Williams and Huang Process Model; CRISP-DM; CRISP-DM extended.

The CRSIP-DM provides a common and well developed framework for performing data mining projects. CRISP-DM identifies 6 steps:

1. Business Understanding
2. Data Understanding
3. Data Preparation
4. Modelling
5. Evaluation
6. Deployment

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