Classification and Regression using Trees
Classification and regression using Decision Trees, Bagged Decision Trees and Random Forests from scratch in python.
Dataset
The attached dataset is about PM2.5. Training Data: Two alternate years is taken as train data. Testing Data: Two years of data from the remaining three is taken as test data.
The years are clearly specified in the code and can be changed.
Problem Statement
Implementation of Decision Trees, Bagged Decision Trees and Random Forest for Classification and Regression. The targets are specified below.
Classification
Target Column: Month
Evaluation Metric: Accuracy
Regression
Target Column: PM2.5
Evaluation Metric: MSE
Methodolody and results are present in the report included. Code is commented at the bottom with titles for type of usage. Uncomment and run the necessary parts.