The maximum gain is obtained for the optimal attribute “Gender.” Once we obtain the optimal attribute, the data table is split according to that optimal attribute. In our case, male gender is only associated with pure class Bus, while female still need further split of attribute.
Using this information, we can now update our decision tree. We can add node Gender which has two values of male and female. The pure class is related to leaf node, thus male gender has leaf node of Bus. For female gender, we need to split further the attributes in the next iteration.
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“We don’t receive wisdom; we must discover it for ourselves after a journey that no one can take for us or spare us.” ― Marcel Proust |