#If none of the above holds true, grow the tree!.#the mode target feature value is stored in the parent_node_class variable.#the direct parent node is that node which has called the current run of the ID3 algorithm and hence.#If all target_values have the same value, return this value.#Define the stopping criteria -> If one of this is satisfied, we want to return a leaf node#.def ID3(data,originaldata,features,target_attribute_name= "class" ,parent_node_class = None ):.Information_Gain = total_entropy - Weighted_Entropy.Weighted_Entropy = np.sum(/np.sum(counts))*entropy(data.where(data=vals).dropna()) for i in range(len(vals))]).
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