shopping basket association rule analysis Using the Internet, locate a sample shopping basket data set. Search terms such as association rule data set or shopping basket data set will yield a number of downloadable examples. With a little effort, you will be able to find a suitable example If necessary, convert your data set to CSV format and import it into your RapidMiner repository. Give it a descriptive name and drag it into a new process window. As necessary, conduct your Data Understanding and Data Preparation activities on your data set. Ensure that all of your variables have consistent data and that their data types are appropriate for the FP-Growth operator. Generate association rules for your data set. Modify your confidence and support values in order to identify their most ideal levels such that you will have some interesting rules with reasonable confidence and support. Look at the other measures of rule strength such as LaPlace or Conviction. Submission Requirements Upload the following 1. The csv file 2. The report with answers to following questions: a. Reference link for the data b. What rules did you find? c. What attributes are most strongly associated with one another? d. Are there products that are frequently connected that surprise you? e. Why do you think this might be? f. How much did you have to test different support and confidence values before you found some association rules? g. Were any of your association rules good enough that you would base decisions on them? Why or why not? h. Export the model as an image and include that image in your report