Question 1

In each assignment you will be able to earn up to 5 marks based on your engagement on the moodle Discussion forums from the topics associated with the given assignment. See the Assignment assessment criteria document for more details.

Question 2

The activities of the instant chat function on a company website were reviewed to identify key features that allowed a given query to be successfully resolved. The data-set Chatter contains the following variables:

• Using only complete records use a combination of figures and text to conduct an exploratory data analysis and summary of the Chatter
• Using a 80:20 train:test split create a decision tree for the Chatter data-set. Explore whether the tree should be pruned. Provide an overview of your results, final decision tree, and a succinct summary of all relevant summary values.
• Fit a bagging OR random forest model using 10-fold cross-validation to the Chatter data-set. Use at least 5 different values for each of the relevant tuning parameters. Provide carefully labeled and well-formatted tables and/or figures as well as an informative summary of your model and results.

Question 3

• Using the same train and test data-sets as Question 2 fit a SVM to the Chatter data-set. Use a range of values to tune the models appropriately. Provide carefully labeled and well-formatted tables and/or figures as well as an informative summary of your model and results.
• Compare and contrast the results and modeling approach of all analyses conducted in both Questions 2 and 3.