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

ODM:
Oracle Data Mining

Having purchased one of the original data mining products (Darwin from Thinking Machines) Oracle Data Miner (ODMiner) has been built from the ground-up, and the data mining engine is integrated into the Oracle server. The Oracle Data Miner is a client-side tool that layers on this server engine. It provides a graphical user interface for data mining using wizards to guide a data miner through the data preparation, data mining, model evaluation, and model scoring process. As the data analyst transforms the data, builds models, and interprets results, Oracle Data Miner can automatically generate code needed to transform the data mining steps into an integrated data mining/BI application. All Oracle Data Mining functions are accessible by PL/SQL and/or Java APIs so you can develop enterprise BI applications on top of your Oracle Database. ODMimer generates Java code from Oracle Data Miner models and results.

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