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:
Variable
Description
Worker
10 point self-assessment score on session given by the employee
Max_msg
Maximum number of characters used in any message
Min_msg
Minimum number of characters used in any message
Exchanges
The total number of messages exchanged during the session
Total_time
Total time the customer was active for
Time_length
Average time (in secs) customer waited for a response from the employee
Age_client
Age of the customer
Resolved
Whether the customer considered the issue resolved (“No” or “Yes”)
(a) Using only complete records - use a combination of figures and text to conduct an exploratory data analysis and summary of the Chatter dataset.
(b) 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.
(c) 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
(a) 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
