An Insurance firm is facing higher claim frequency. The management decides to collect data from the past few years. Make a model using CART, RF & ANN which predicts the claim status and provide recommendations to management. Use CART, RF & ANN and compare the models' performances in train and test sets.

a)Split the data into test (30%)and train (70%).

b) Build classification model for CART, Random Forest & Artificial Neural Network

b)Check the performance of Predictions on Train and Test sets for CART, Random Forest & Artificial Neural Network.

c) Draw Confusion Matrix, Plot ROC / AUC curve and get ROC/ AUC score for each model

d)Compare all the model

Dataset for Problem https://drive.google.com/file/d/1t83A6DZB7TI7dU_J7NJFEgt6GHTshVlY/view?usp=sharing

AttributeInformation:

1. Target: Claim Status (Claimed)

2. Code of tour firm (Agency_Code)

3. Type of tour insurance firms (Type)

4. Distribution channel of tour insurance agencies (Channel)

5. Name of the tour insurance products (Product)

6. Duration of the tour (Duration)

7. Destination of the tour (Destination)

8. Amount of sales of tour insurance policies (Sales)

9. The commission received for tour insurance firm (Commission)

10. Age of insured (Age)