DATA MINING Desktop Survival Guide by Graham Williams
Desktop Survival Project Home List of Figures List of Tables Data Mining Introduction Data Mining with Rattle Data Exploring Data Transforming Data Cluster Analysis Association Analysis Classification and Regression Models Evaluation and Deployment Issues Moving into R Troubleshooting Beyond Rattle R 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 GTK, R, and Rattle Glossary Bibliography Index

Mosaic Plot

Figure 4.3: Mosaic plot of Age by Adjusted.

A mosaic plot is an effective way to visualise the distribution of the values of a variable over the different values of another variable. Often, this second variable is the target variable that we are interested in (e.g., XnullXRattle!VariablesR functions (R function)Rattle!VariablesR libraries (R library)Rattle!VariablesR option (R option)Rattle!VariablesR packages (R package)Rattle!VariablesDatasets (Dataset)Rattle!VariablesRattle!VariablesAdjusted in our audit).

The example in Figure 4.3 displays the relationship between the input variable XnullXRattle!VariablesR functions (R function)Rattle!VariablesR libraries (R library)Rattle!VariablesR option (R option)Rattle!VariablesR packages (R package)Rattle!VariablesDatasets (Dataset)Rattle!VariablesRattle!VariablesAge and target variable XnullXRattle!VariablesR functions (R function)Rattle!VariablesR libraries (R library)Rattle!VariablesR option (R option)Rattle!VariablesR packages (R package)Rattle!VariablesDatasets (Dataset)Rattle!VariablesRattle!VariablesAdjusted. XnullXRattle!VariablesR functions (R function)Rattle!VariablesR libraries (R library)Rattle!VariablesR option (R option)Rattle!VariablesR packages (R package)Rattle!VariablesDatasets (Dataset)Rattle!VariablesRattle!VariablesAge is a numeric variable, so for it to make sense in a mosaic plot we need to bin it so that it becomes categoric, which can be accomplished using the Remap option of the Transform tab. In this case we have transformed XnullXRattle!VariablesR functions (R function)Rattle!VariablesR libraries (R library)Rattle!VariablesR option (R option)Rattle!VariablesR packages (R package)Rattle!VariablesDatasets (Dataset)Rattle!VariablesRattle!VariablesAge into 6 quantiles (equal sized groups).

The plot tells us that XXXX

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