Question

Problem 1: CART Given dataset below you want to build a regression tree, where x1 and x2 are the features and y is the label. x1 x2 y -2 8 positive 3 4 negative 12 6 positive 2 3 negative 8 -4 positive 6 3 positive (a) Which feature(x1 or x2) would you use as your first split on your decision tree, why? (b) Draw the regression tree built by the ID3-Algorithm introduced in class (c) If we add a new categorical feature x3 as seen below, how would you account the new change? (Hint: think about what it means for the algorithm to \"split\" on a categorical feature.) x1 x2 x3 y -2 8 B positive 3 4 R negative 12 6 G positive 2 3 R negative 8 -4 B positive 6 3 G positive

          Problem 1: CART
Given dataset below you want to build a regression tree, where x1 and x2 are the features and y is
the label.
x1 x2 y
-2 8 positive
3 4 negative
12 6 positive
2 3 negative
8 -4 positive
6 3 positive
(a) Which feature(x1 or x2) would you use as your first split on your decision tree, why?
(b) Draw the regression tree built by the ID3-Algorithm introduced in class
(c) If we add a new categorical feature x3 as seen below, how would you account the new change?
(Hint: think about what it means for the algorithm to \"split\" on a categorical feature.)
x1 x2 x3 y
-2 8 B positive
3 4 R negative
12 6 G positive
2 3 R negative
8 -4 B positive
6 3 G positive

Problem 1: CART
Given dataset below you want to build a regression tree, where x1 and x2 are the features and y is
the label.
x1 x2 y
-2 8 positive
3 4 negative
12 6 positive
2 3 negative
8 -4 positive
6 3 positive
(a) Which feature(x1 or x2) would you use as your first split on your decision tree, why?
(b) Draw the regression tree built by the ID3-Algorithm introduced in class
(c) If we add a new categorical feature x3 as seen below, how would you account the new change?
(Hint: think about what it means for the algorithm to s̈plitön a categorical feature.)
x1 x2 x3 y
-2 8 B positive
3 4 R negative
12 6 G positive
2 3 R negative
8 -4 B positive
6 3 G positive

Added by Jose J.

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