Run the Nearest Neighbor classifier with a k-value of 7 and a Support Vector Machine with...

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Run the Nearest Neighbor classifier with a k-value of 7 and a Support Vector Machine with...

Run the Nearest Neighbor classifier with a k-value of 7 and a Support Vector Machine with default values using 10-folds cross validation on the diabetes data set (diabetes.arff available online) in Weka. Fill in the confusion matrices for the models in the tables below and use the cost matrix to compute the cost for each model. Based upon the cost, which model should be selected and why?

Nearest Neighbor (k=7) Confusion Matrix

	Tested Negative	Tested Positive
Tested Negative
Tested Positive

Support Vector Machine Confusion Matrix

	Tested Negative	Tested Positive
Tested Negative
Tested Positive

Cost Matrix

	Tested Negative	Tested Positive
Tested Negative	0	50
Tested Positive	100	-1

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Based on the cost, Support vector machine model must be selected since its F-measure is high

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