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

Downloading the Data