lahirukumarahewagama / cs4622-machine_learning-mini_project

CS4622-Machine_Learning-Mini_Project Kaggle Competition

CS4622-Machine_Learning-Mini_Project

Kaggle Competition : https://www.kaggle.com/competitions/amex-default-prediction/overview

American Express is a globally integrated payments company. The largest payment card issuer in the world, they provide customers with access to products, insights, and experiences that enrich lives and build business success.

In this competition, you’ll apply your machine learning skills to predict credit default. Specifically, you will leverage an industrial scale data set to build a machine learning model that challenges the current model in production. Training, validation, and testing datasets include time-series behavioral data and anonymized customer profile information. You're free to explore any technique to create the most powerful model, from creating features to using the data in a more organic way within a model.

Techniques Used

preprocessing

• Imputation
• Discretization
• Variable Transformations
• Normalization Techniques
• Remove highly correlated features

feature engineering techniques

• Creation of new features
• Target Encoding
• Lable Encoding
• OrdinalEncoder
• Feature Importance
• Feature Selection

Algorithum

• SVM (Support Vector Machine)
• KNN (k-nearest neighbors)
• XGBoost (X Gradient-Boosting)
• LGBM (Light Gradient-Boosting )