XGBoost Model Tuning
Dataset: Imbalanced Binary Classification Credit Dataset
Objective is to tune XGBoost model to accurately predict both class using Test dataset. Please find classes and metrics below. I am also sending over the dataset for both training and testing. Feel free to change ratio for training to testing data as you must to achieve optimal outcome. Please use Jupyter Notebook attached to make revisions.
Y Class Predictions:
'[login to view URL]' = 1
''[login to view URL]' = 0
Evaluation Metrics:
Test ROC AUC > 80%
Accuracy > 80%
I would like to maximize both evaluation metrics in their respective orders above. All data and code written and used will be reserved under my ownership.
I would also like an explanation of changes made. Looking for a one day turnaround.