DATA MINING Desktop Survival Guide by Graham Williams
Desktop Survival Project Home Rattle Introduction Getting Started Interacting with Rattle Data Exploring Data Test Transforming Data Cluster Analysis Data Graphics in R Understanding Data Preparing Data Descriptive and Predictive Analytics Issues Evaluating Models Reporting Cluster Analysis Text Mining Text Mining Algorithms Bagging Bayes Classifier Cluster Analysis Conditional Trees Hierarchical Clustering K-Nearest Neighbours Linear Models Neural Networks Support Vector Machines 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 Installing Rattle Glossary Bibliography Index

I

Independent Variable: The classical term for an Refer[input-variable]input variable.

Input Variable: The Refervariables of a dataset that are generally measurable or preset, and used as the input to the modelling and mining. It is synonymous with the statistical term Referpredictor and the classical term independent variable. See also Output Variable.

Interestingness: A measure used to rank or filter discoveries, particularly in the context of the often overwhelming number of discoveries that typical data mining tools present the user, with example measures including Refersupport, Referconfidence, Referlift, and Referleverage. See also Refer[subjective-interestingness]subjective interestingness, Refer[objective-interestingness]objective interestingness.

Invariant Clustering:

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