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 Minimal Distance Classifier
(MDC) to classify P using the training data shown in Table.
2. Consider the three-class data set shown in the following table. Let the
patterns be considered in the order X1 to X12. What is the resulting
Condensed set?
3. Consider a two-class problem with the following training dataset.
Class1 : 1 : (1, 2), 2 : (2, 2), 3 : (2, 1) Class2 : 4 : (2.7, 2), 5 :
(4, 2), 6 : (4, 1). Obtain the Condensed set if we process the data in
the order 1, 2, 3, 4, 5, and 6. What happens if we consider the data in
the order 2, 3, 1, 4, 5, and 6?
4. Use the MNNC to obtain Condensed using the data given in problem
5. Use each class as a cluster in the data given problem 1. Use the cluster
centroids as prototypes and classify pattern P = (3, 2)t.
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