BA-Project-Mgt-Hotel-Booking-Cancellation-Prediction-Project

CRISP-DM

1. EDA
2. Data Cleaning (Detect Missing Values and Outliers, Data Pipeline, Transformation)
3. Supervised Machine Learning Modeling (Naive Bayes, Logistic Regression, Neural Network, Random Forest, Gradient Boosting Decision Tree, K-Nearest Neighbors)
4. Evaluation (10-Fold Cross-validation, Confusion Matrix [Accuracy, Precision, Recall, Specificity, F1 Score], AUC-ROC Curve, Cumulative Gain and Lift Charts)
5. Model Explainability (Relative Feature Importance, Partial Dependencies, SHAP Values)