[Solved] CS60050 Assignment 1- Decision trees

1. Build a decision tree by taking as input a maximum depth and by randomly splitting the dataset as 80/20 split i.e., 80% for training and 20% for testing. Provide the accuracy by averaging over 10 random 80/20 splits. Consider that particular tree which provides the best test accuracy as the desired one.
2. What is the best possible depth limit to be used for your dataset. Provide a plot

explaining the same.

3. Perform the pruning operation over the tree obtained in question 2 using a valid

statistical test for comparison.

4. Print the final decision tree obtained from question 3 following the hierarchical levels of

data attributes as nodes of the tree.

5. A brief report explaining the procedure and the results

Dataset:

1. COVID-19 percentage rate (aggregated):

It contains the time-series percentage increase in COVID-19 cases worldwide. The attributes are date, confirmed cases, recovered cases, number of deaths, and increase rate of confirmed cases. Target attribute is the rate of increase in confirmed cases. Filename: PercentageIncreaseCOVIDWorldwide.csv