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This is the first release of Interactive Decision Trees package. It contains Python modules that enable the user to interact with the Decision Tree by creating new composite variables, grouping the input variables and color code the groups, selecting important variables, manually change variable and threshold to split, manually change leaf node class and manually prune the Decision Tree. Moreover, it contains a graphical user interface in Jupyter Lab notebook for supporting the user-decision tree interactions.
Human in the loop, Interactive Machine Learning, Interpretability, Interactive Decision Trees
Human in the loop, Interactive Machine Learning, Interpretability, Interactive Decision Trees
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