Classification Tree

This workflow combines the inference and visualization of classification trees with a scatterplot. When both the tree browser and the scatterplot are open, selection of any node of the tree sends the related data instances to scatterplot. In the workflow, the selected data is treated as a subset of the entire data set and is highlighted in the scatterplot. With simple combination of widgets we have constructed an interactive classification tree browser.

File

Classification Tree

Classification Tree Viewer

Scatter Plot

Box Plot

Load data on Iris ("iris.tab") from preloaded documentation data sets.
Any change in selection of the tree node changes the rendering in the scatter plot.
Double-click on this widget and select any node in the tree.
The data selected in the tree viewer propagates to all the downstream widgets in the workflow.
This workflow works best if you have Tree Viewer, Scatter Plot and Box Plot all open at the same time.
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{'limit_min_leaf': True, 'model_name': 'Classification Tree', 'min_leaf': 2, 'attribute_score': 0, 'max_depth': 100, 'limit_min_internal': True, 'min_internal': 5, 'savedWidgetGeometry': None, 'limit_depth': True}
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{'compare': 1, 'sig_threshold': 0.05, 'stretched': True, 'context_settings': [], 'show_annotations': True, 'savedWidgetGeometry': None, 'stattest': 0}