Text Mining and Visualization

78 Text Mining and Visualization: Case Studies Using Open-Source Tools

The data set is then split up into a training (70%) and test set (30%). A decision tree

is trained on the training set and scored on the test set. The accuracy of the decision

tree model is 93.667%. Figure 3.13 shows the confusion matrix of the scorer node. The

FIGURE 3.13: Confusion matrix and accuracy scores of the sentiment decision tree model.

corresponding receiver operating characteristics curve can be seen in Figure 3.14.

FIGURE 3.14: ROC curve of the sentiment decision tree model.

The aim of this example application is to clarify and demonstrate the usage of the

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