Hotel booking demand
This notebook is covering following topics.
- Problem statement
- Downloading the data
- Exploratory data analysis and visualisation
- Preprocessing and Feature Engineering
- Imputing and scaling numerical data
- Encoding categorical data
- Training and evaluating Logistic Regression Model
- Training and evaluating Decision Tree Model
- Training and evaluating Random Forest Model
- Making Predictions on New Inputs
- Saving and Loading Trained Model
Problem Statement
Objective: Predict the probability of booking cancellation.
Context
Have you ever wondered when the best time of year to book a hotel room is? Or the optimal length of stay in order to get the best daily rate? What if you wanted to predict whether or not a hotel was likely to receive a disproportionately high number of special requests?
This hotel booking dataset can help you explore those questions!Content
This data set contains booking information for a city hotel and a resort hotel, and includes information such as when the booking was made, length of stay, the number of adults, children, and/or babies, and the number of available parking spaces, among other things.
Source of data: https://www.kaggle.com/jessemostipak/hotel-booking-demand