Project $2$ CMPSCI $4342/5342-60$ points

Develop a decision tree analysis pipeline for a classification problem in python,

incorporating pruning techniques for dataset $($attached with the project$).$

Data Preprocessing: Perform any preprocessing required including normalization,

handling missing values, and feature scaling. $(5$ points$)$

Model Training: Train a decision tree classifier with an extensive range of

hyperparameters $($e$.$g$.,$ maximum depth, minimum samples split, minimum samples

leaf, maximum features$).$ Implement tuning for criteria like entropy and Gini impurity.