This is the link for the dataset: 
https://drive.google.com/file/d/1vbVR9PYKsQSuipfPrg9YfpB5tJIDbsYs/view?usp=share_link

For this midterm, your task is to experiment with different techniques for handling imbalanced datasets, including under-sampling and over-sampling methods. Specifically, you will be testing the following techniques: Condensed NearestNeighbour TomekLinks OneSidedSelection Edited NearestNeighbours Repeated Edited NearestNeighbours AIIKNN RandomOverSampler SMOTE You can access the necessary code to implement and test these tools on Canvas, where the dataset will also be available. To complete this assignment, you are required to submit a report, the details of which are outlined in these slides. Rubric Pre-processing It needs to be done correctly Testing under and over-sampling Experiments You will use Random Forest classifier for this midterm The experiments will focus on using and reporting the results of the sampling techniques You need to be able to explain the "whys" of your results