Python problems.

CSI 5810 (Assignment # 3)

1. The following examples from a two-class classification problem are given:

Class1: [2 2]T, [3 5]T; Class 2 [1 3]T, [-1 -0.5]T

Starting with an augmented weight vector, [1 1 1]T, determine a solution vector for above data using the perceptron learning rule. Show first five steps of weight vector updating.

2. Consider the following eight records; each record is described by two quantitative attributes:

A = (2, 10)t, B = (2, 5)t, C = (8, 4)t, D = (5, 8)t, E = (7, 5)t, F = (6, 4)t G = (1, 2)t, H = (4, 9)t.

Let records “A”, “B”, “G”, and “H” be from class 1 and the remaining four records from class 2. Using this information, construct the Fisher’s linear discriminant function for this problem and determine the class label for the point M = (3, 3)t.

3. Consider the following six examples with three attributes:

Example #	Color	Shape	Size	Class
1	Red	Square	Big	+
2	Blue	Square	Big	+
3	Red	Round	Small	-
4	Green	Square	Small	-
5	Red	Round	Big	+
6	Green	Square	Big	-

Determine the best attribute for root node of a decision tree classifier for above data. Use Gini index for attribute selection.