JMP-classification-assignment.pdf - For this part you will...

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For this part, you will use JMP Pro to build and test five classifier models – Naïve Bayes, KNN, Partition (decision tree), Boosted Tree, and Neural Network. Follow the instruction given below. You will use german-bank.jmp dataset for all five models. For more details about how to use each classifier model, refer to Predictive and Specialized Modeling.pdf documentation. (1). Naïve Bayes Start JMP Pro Open german-bank.jmp Select Analyze > Predictive Modeling > Naïve Bayes Select checking through foreign and click X,Factor Select class and click Y,Response Select Validation (on the left) and click Validation (on the right) Click OK. You will see Naïve Bayes Report (or output) that is similar to Figure 9.1 in Predictive and Specialized Modeling.pdf documentation. Capture the report screen and paste it in your submission. The dataset’s class attribute has two possible values – 1 and 2. Using the confusion matrix of Validation in the report (There are two confusion matrices. Make sure that you use the Validation confusion matrix), calculate the following measures for both classes (similar to those in Weka’s output window): TP Rate FP Rate Precision Recall F-Measure Class 1 2 (2). KNN Start JMP Pro Open german-bank.jmp
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  • Fall '19
  • Statistical classification, JMP Pro

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