Read Chapter 5 on Performance Evaluation and Chapter 15 on Cluster Analysis thoroughly and then discuss the following subjects in detail: teaching it to your classmates as though they had never read the chapters and you can use bullet points.
1)Describe and explain the measures used to evaluate the performance of predictive models. Why you need to use the validation dataset to evaluate models?
2)Describe and explain the terms misclassification error, accuracy, propensities, cutoff value, sensitivity, and specificity. Explain why you want to use cutoff values different from 0.5 if they increase the misclassification rate?
3)How does the hierarchical clustering algorithm work? Describe what is a dendrogram and how to use it. Describe how to validate clusters. Summarize the advantages and weaknesses of hierarchical clustering.
