Learning for Numeric Prediction
(a) Let the weights of a two-input perceptron be: w0 = 0:2, w1 = 0:5 and w2 = 0:5. Assuming that x0 = 1, what is the output of the perceptron when:
[i] x1 = 1 and x2 = 1 ?
[ii] x1 = 1 and x2 = 1 ?
Letting w0 = 0:2 and keeping x0 = 1, w1 = 0:5 and w2 = 0:5, what is the perceptron output when:
[iii] x1 = 1 and x2 = 1 ?
[iv] x1 = 1 and x2 = 1 ?
(b) Here is a regression tree with leaf nodes denoted A, B and C:
X <= 5 : A
X > 5 :
| X <= 9: B
| X > 9: C
This is the training set from which the regression tree was learned
X Class
1 8
3 11
4 8
6 3
7 6
8 2
9 5
11 12
12 15
14 15
Write down the output (class) values and number of instances that appear in each of the leaf nodes A, B and C of the tree.