3. [40 marks] Manually train a decision tree based on the following dataset. a) Please show the detailed process of selecting an attribute to split the instance set at every node. Gini index should be used to measure the impurity (30 marks). b) Draw the final decision tree (5 marks). c) Classify the test instance x = (x1 = large, x2 = hot, x3 = high, x4 = false) (5 marks). x1 x2 x3 x4 y small hot high false no small hot high true no medium hot high false yes large mild high false yes large cold low false yes large cold low true no medium cold low true yes small mild high false no small cold low false yes large mild low false yes small mild low true yes medium mild high true yes medium hot low false yes large mild high true no

3. [40 marks] Manually train a decision tree based on the following dataset. a) Please show the detailed process of selecting an attribute to split the instance set at every node. Gini index should be used to measure the impurity (30 marks). b) Draw the final decision tree (5 marks). c) Classify the test instance x = (x1 = large, x2 = hot, x3 = high, x4 = false) (5 marks). x1 x2 x3 x4 y small hot high false no small hot high true no medium hot high false yes large mild high false yes large cold low false yes large cold low true no medium cold low true yes small mild high false no small cold low false yes large mild low false yes small mild low true yes medium mild high true yes medium hot low false yes large mild high true no