Given the data set below for the binary class problem. Keep 2 decimal places. ID Attribute...

 

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Given the data set below for the binary class problem. Keep 2 decimal places. ID Attribute A Attribute B Attribute C Class label 1 T F 2 T T T T T T F F 3 4 5 6 7 9 10 F T F T F F F T F 3.5 2.0 6.7 5.5 4.8 2.3 3.7 4.0 5.1 Y Y Y N Y N ZZZZ N N N N (a) Calculate the information gain when splitting on attribute A and B. Which attribute would the decision tree induction algorithm choose? Show all your work. [10] (b) Calculate the reduction in impurity using Gini index when splitting on A and B. Which attribute would the decision tree induction algorithm choose? Show all your work. [10] (c) Compare information gain and Gini index. Explain your results in part (a) and (b). [5] (d) For the attribute C, which is a continuous attribute, describe how you compute the information gain. [5] Given the data set below for the binary class problem. Keep 2 decimal places. ID Attribute A Attribute B Attribute C Class label 1 T F 2 T T T T T T F F 3 4 5 6 7 9 10 F T F T F F F T F 3.5 2.0 6.7 5.5 4.8 2.3 3.7 4.0 5.1 Y Y Y N Y N ZZZZ N N N N (a) Calculate the information gain when splitting on attribute A and B. Which attribute would the decision tree induction algorithm choose? Show all your work. [10] (b) Calculate the reduction in impurity using Gini index when splitting on A and B. Which attribute would the decision tree induction algorithm choose? Show all your work. [10] (c) Compare information gain and Gini index. Explain your results in part (a) and (b). [5] (d) For the attribute C, which is a continuous attribute, describe how you compute the information gain. [5]

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This image contains a table with data for a binary class problem and four tasks requiring analysis of this data To walk you through the calculations for each of these tasks lets take a look at the tab... View the full answer