Parameter Sweep over Decision Trees (using python) - Dataset: https://www.kaggle.com/uciml/mushroom-classification - Divide it randomly into 65% training and 35% test data - Build a Decision Tree classifier with the following hyper-parameter combinations: o (Im)Purity Measure: Entropy o Maximum Depth:1, 2, 3, 4, 5, 6, 7 o Purity Threshold: 0.6, 0.7, 0.8, 0.9 o Size Threshold: Very low - Create a 2-D Table (Depth vs. Purity) above values - In each cell, write the Training and Test accuracy - Make an observation about the best parameter combination - Draw the decision tree using the tools available - Write down the rules learnt by this decision tree