Guided Inquriy 15: Classification evaluation algorithms

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Then complete and/or modify your code from Class Activity 14: kNN Evaluation. Then, update your implementation to support multi-class classification. That is, for each of the distinct class labels, display the evaluation measure with it as the positive class.

For example, inputting a classification of the Iris data set, which has three distinct class labels (virginica, satosa, and versicolor), would have three evaluation sections (one for each of the three distinct class labels) listing all of the evaluation measures (tp, fp, tn, fn, accuracy, precision, recall, and F1).

Remember you may work on this with others. Post questions you have to Piazza.

Submit your code when you're finished.