For this page you will need to refer to your decisions from Decision Tree: Predicting Shopping Behavior — Part 2.
Build and Understand the Tree
Complete the tree (left), then fill in the blanks (right).
|
1 The root node of this tree is .
2 The first set of branches includes: 3 Write the rules that this decision tree follows. Predict that: |
Test the Tree
4 Below is a new set of potential customers. Use the decision tree and rules above to predict whether or not they will buy the game.
| name | age | shopping history | interest in game | buys game | model predicts |
|---|---|---|---|---|---|
Kat |
teen |
new customer |
yes |
yes |
|
Billy |
twenties |
new customer |
no |
no |
|
Chen |
twenties |
previous customer |
no |
no |
5 Compare the "buys game" column with the predictions. For which customers was the computer correct? Kat Billy Chen
6 Should we change any of our rules based on the addition of this new data? Why?
Reflect
7 Our rules made 100% accurate predictions with our training dataset, but were only 33% accurate with our test dataset. Why?
8 What could we do to improve the quality of this decision tree?
These materials were developed partly through support of the National Science Foundation, (awards 1042210, 1535276, 1648684, 1738598, 2031479, and 1501927). 
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