Travel Insurance Prediction

• This project was carried out with the aim to build and find Machine learning model that have good result to predict whether someone will buy Travel Insurance packages or not
• Because in imbalanced data condition, F1 score is the proper metric to measure the model performance

Dataset Content

The dataset contains some information about :

Data Cleaning

• Split dataset into Training and Test (70%:30%)
• Missing Values Checking
• Duplicates Checking and Handling
• Outlier Checking
• Feature encoding

Modelling

• Split Data training and test to X & y
• Use Oversamping and set threshold to handling imbalanced data
• Find the right Model based on the best F1 score