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

V

Validation Set: A portion of a dataset that is used to test the performance of a model as it is being built. See also Training Set and Refer[testset]Test Set.

Variance: The error in a model due to the fact that the model is built from only a sample of the data taken to represent the whole population. That is, those instances occasionally incorrectly classified by models built by the learning algorithm. Modelling error due to variance can be reduced using Bagging. Compare with Refer[bias]bias.

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