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 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 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 Installing Rattle Bibliography Index

Building Our First Model

TODO: Now click on the Model tab, and click Execute again.

We have now loaded the weather.csv dataset and are ready to build a model or two. Simply click the Model tab to be presented with the Model options that we see in Figure 4. To build a decision tree model, one of the most common data mining models, simply click the Execute button, and we will see the results displayed, as in Figure 4.

Figure 4: The weather dataset has been loaded and a decision tree model has been built. The textview here shows a textual representation of the decision tree. With a little study you should be able to make sense of some of it!

Click on the Draw button for a picture of the decision tree.

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