This exercise considers $\chi^2$ pruning of
decision trees (Section chi-squared-section

. 1. Create a data set with two input attributes, such that the information gain at the root of the tree for both attributes is zero, but there is a decision tree of depth 2 that is consistent with all the data. What would $\chi^2$ pruning do on this data set if applied bottom up? If applied top down?

2. Modify DECISION-TREE-LEARNING to include $\chi^2$-pruning. You might wish to consult Quinlan [Quinlan:1986] or [Kearns+Mansour:1998] for details.

. 1. Create a data set with two input attributes, such that the information gain at the root of the tree for both attributes is zero, but there is a decision tree of depth 2 that is consistent with all the data. What would $\chi^2$ pruning do on this data set if applied bottom up? If applied top down?

2. Modify DECISION-TREE-LEARNING to include $\chi^2$-pruning. You might wish to consult Quinlan [Quinlan:1986] or [Kearns+Mansour:1998] for details.

.
1. Create a data set with two input attributes, such that the
information gain at the root of the tree for both attributes is
zero, but there is a decision tree of depth 2 that is consistent
with all the data. What would $\chi^2$ pruning do on this data set
if applied bottom up? If applied top down?

2. Modify DECISION-TREE-LEARNING to include $\chi^2$-pruning. You might wish to consult
Quinlan [Quinlan:1986] or [Kearns+Mansour:1998] for details.