ML Project: Hotel Cancellation Prediction

UPenn CIS520 Machine Learning class project: utilize different machine learning approaches to predict the hotel booking's cancellation.

Authors: Yifei Li, Zhijian Yang

Links

• PDF: Project Report
• Notebooks: Dataset Cleaning and Visualization
• Notebooks: Basic Models Experiment
• Notebooks: Advanced Models Exploration
• Dataset: Raw [1]
• Dataset: Processed

The latex code of report is here; and the related kaggle is here.

Problem Formulation

Binary classification:

• Predict: IsCancelled or not: y={0,1} with dim=2
• Observations: processed feature set: X with dim=194

Models

• Deep Factorization-Machine (half-done)
• Soft-Voting Ensemble Estimator
• Neural Network (vanilla and tuned)
• Random Forest (vanilla and tuned)
• Decision Tree
• XGBoost
• AdaBoost
• Extra Trees
• SVM (vanilla and tuned)
• Logistic Regression (baseline)

References

[1] Nuno Antonio, Ana de Almeida, and Luis Nunes. Hotel booking demand datasets. Data in Brief, 22:41 – 49, 2019.

Credits

• Source of the background picture: Four Seasons Hotel in Guangzhou