Predictive and Classification Modeling: German Credit and Airfare Datasets

Classification

This assignment asks you to take datasets and create predictive and classification models.

For the classification exercise use the German Credit dataset referenced in Question 11. For this dataset:
·Perform the data preparation steps as indicated in the text.
·Perform k-NN classification.
·Perform Bayes classification.
·Perform Tree classification.
·Perform Regression classification.
·Perform Neural Network classification.
·Choose the best model and justify why.

For the prediction model use the Airfare dataset referenced in Question 8. For this dataset:
·Perform the data preparation steps as indicated in the text.
·Perform k-NN prediction.
·Perform Tree prediction.
·Perform Regression prediction.
Choose the best model and justify why it is the best.

The deliverables for this assignment are:
·A written report. The report should contain sections for each of classification and prediction showing:
oThe summary results tables that were generated by each of your models.
oScreenshots of the configuration window(s) for each model.
oYour choice of the most suitable model for each of classification and prediction and the justification why that is the one that you chose. (Likely a couple of paragraphs for each of prediction and classification)
·Your spreadsheet(s).

·10% of the assignment’s marks for each of the 8 models outlined above being successfully run.
·10% for each of the justification written pieces.