Python implementation of Decision Tree. (a practice)

from DecisionTree import *

dt = DecisionTree(method="C4.5", max_depth=3)

Parameters -

• method (string) “ID3”,or “C4.5”
• max_depth (int) the maximum depth of the tree

dt.fit(X, y)

Parameters -

• X (pandas.DataFrame) attributes of samples
• y (pandas.DataFrame) labels of samples, must have the same number of rows as X  

dt.exportTree()

Example output -

--- [Outlook]
    --- overcast
        ===> yes
    --- rain
        --- [Wind]
            --- high
                ===> no
            --- low
                ===> yes
    --- sun
        --- [Humidity]
            --- <77.5
                ===> yes
            --- >=77.5
                ===> no

y_pred = dt.predict(X)

Parameters -

• X (pandas.DataFrame) attributes of samples

Return -

• y_pred (list) prediction of labels for each sample