Assignment
1. Let the training set consist of patterns in the following table. Let the
test patten be P = (3.0, 2.0)t. Use the NNC to classify P using the
training data shown in Table.
2. Classify test pattern P in problem 1 using the kNNC with k = 5.
3. Solve problem 2 using the test pattern (4.2, 1.8)t.
4. Solve problems 2 and 3 using modified k-nearest neighbour classifier.
5. Use Fuzzy kNN algorithm to classify P using m = 2 and the data given
problem 1.
6. Use the r-Near Neighbours classifier with r = 1.45, 5 neighbours, and
data in problem 1 to classify P.
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