ML.Classification

The extra points project for the midterm exam as follows

1. Process the dataset (select 1 of the 4) provided (https://archive.ics.uci.edu/ml/datasets/Bank+Marketing) by applying and comparing accuracies of kNN, DT, Naïve-base, LRM, Logit.
2. Check dataset and do preprocessing (missing value interpretation, transformations etc)
3. Show the scatter plot and display correlations for those features whose correlation is higher than 0.6. Do everything in one scatter plot.
4. Try different variations and parameters for above algorithms and check metrics. For example kNN with k=3,5,9, various DTs, NBs and RMs etc
5. Display accuracies for each different variation. For example: applied transformation check the metrics etc.,
6. You can implement program in menu based form
7. Prepare explanatory document and present in the class
8. For the grade document and program must be submitted to instructor for check. This project is individual