By using benchmark classical dataset.
implement a python code for decision tree that deal with the unknown attribute values by assign probability pi to each possible value vi of A assign fraction pi of example to each descendant in tree and edit the same code to deal with the unknown value by : 1- Assign most common value of A among other examples with same target value 2- If node n tests A , assign most common value of A among other examples sorted to node n then do a comparison between the three ways.
Kindly edit the same code
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