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

Statistica Data Miner:
From StatSoft

STATISTICA Data Miner combines a comprehensive selection of data mining tools with an icon-based interface. It targets integrated data mining solutions in a variety of business domains such as finance, marketing, insurance, and pharmaceuticals. The included data mining tools integrate with the STATISTICA line of products which includes a web delivery application. The provided algorithms cover the whole spectrum of data mining technologies including alternative neural networks architectures, classification/regression trees, multivariate modelling, and many other classification and regression techniques. User implemented nodes can easily be added to the interface and many models generate industry standard PMML (XML).

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