DATA MINING Desktop Survival Guide by Graham Williams
Desktop Survival Project Home List of Figures List of Tables Rattle Introduction Getting Started Interacting with Rattle Data Loading Data Exploring Data Test Transforming Data Cluster Analysis Evaluation and Deployment Issues Moving into R Troubleshooting Beyond Rattle R Getting Help Data Graphics in R Understanding Data Preparing Data Descriptive and Predictive Analytics Issues Topics in Data Mining Archetype Analysis Text Mining Algorithms Bagging Bayes Classifier Cluster Analysis Conditional Trees Hierarchical Clustering K-Nearest Neighbours Linear Models 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 Appendices Installing Rattle Bibliography Index

Nolan Groups

Nolan Groups work by finding the minimum value of a variable for the observations in a group and allocates it a value of 0.01 and the maximum value and allocates it a value of 99.9. All values in between are allocated a new value which is representational of the position and rank in the original variable. When used in conjunction with a categoric variable, the observations are segmented by the values of the categoric variable and all values within the group are then transformed using the minimum value and allocates it a value of 0.01 and the maximum value and allocates it a value of 99.9. All values in between are allocated a new value which is representational of the position and rank in the original variable.

Nolan Groups is a methodology that applies the theory of relativity to analytics, by transforming measurement variables between 0.01 and 99.9 to a specific subset of bins's which represent sub populations identified by their association with a value within a categorical variable. By using this transformation, observations are specifically assigned to a position within the sample, that represents their position relative to only other observations within the same bin.

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