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

F

Fuzzy Expert System: Uses Refer[fuzzy-logic]Fuzzy Logic instead of Boolean Logic for reasoning in an Expert Systems.

Fuzzy Logic: Introduced by Dr. Lotfi Zadeh of UCB around 1960. A superset of conventional Boolean logic that allows truth values in the interval $[0,1]$, instead of just the set $\{0, 1\}$ with a rigorous set of mathematical operations that define how the logic system works. The most common definitions for the basic operations are:

$$truth(x AND y) = min (truth(x), truth(y)); truth(x OR y) = max (truth(x), truth(y)); truth(NOT x) = 1 - truth(x),$$

where x and y are truth values (degree of belief, degree of membership).

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