ProfitForBrescia

#machine learning,#Booking cancellation,#Brescia Norton Hotel,#Profit Brescia Norton Hotel,#sklearn,#hypertuning,#Algorithms,#Accuracy

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Inspiration

We have a deep interest in machine learning concepts and to develop more machine learning projects.We have an expertise knowledge in machine learning and deep learning which made us to do this project.Analysing the given problem statement and the dataset plays a major role in developing this project.

About Brescia Norton Hotel

With a history spanning more than 60 years, the Brescia Norton Hotel is a well-known, five-star luxury hotel. Unfortunately, the hotel has recently encountered a number of difficulties, the most important of which is the rising rate of reservation cancellations. The hotel suffered its largest-ever loss of $124,000 in February as a result of a record-breaking 38 room cancellations.

Problem statement

The management team of the hotel determined that the problem of anticipating and managing reservation cancellations necessitates an urgent remedy. Booking cancellations have an impact on the hotel's revenue as well as its ability to operate efficiently. For instance, based on anticipated demand, cleaning and front desk employees, goods, and facilities must be assigned, and when reservations are cancelled, these resources sit underutilised, contributing to financial loss.One in four hotel visitors cancel their reservations before their stay, making the Brescia Norton Hotel believe that high cancellation rates in hotels are the new industry standard. This is a completely incorrect assumption made in light of the rising cancellation trend from year to year. This cancellation tendency has an impact on the hotel's inability to predict occupancy effectively within their revenue management, and it also results in a loss of opportunity cost for the hotel (unsold room due to cancellation)

Objectives

This project's objectives are to conduct an exploratory data analysis to identify the characteristics of consumers who cancel and to identify a pattern in cancelled bookings.Developing a classification machine learning model with an accuracy score of 0.75 to 0.9 to forecast cancellation.

What it does

We have given a dataset to train and test the model.Our project predicts the number of bookings cancelled.Our project finds out the characteristic of customers who cancelled and finding a pattern in cancelled booking by doing an exploratory data analysis

How we built it

We built it in colab and we have used libraries such as sklearn,numpy,pandas etc..We have used some machine learning algorithms such as LogisticRegression,KNN,Decision Tree,RandomForest,XGB

Challenges we ran into

At first,analysing the dataset given in the dataquest took us more time.We came with many errors while building our model.It took more time for data cleansing and training the dataset.

Accomplishments that we're proud of

We are happy to say that our project stock market analysis using machine learning has won a prize of $2500 in daisi hackathon via hackerearth.The same project has also won the best finance hack category in codewithHarnoor 2.0 via devpost

What we learned

We had a deep analysis on hotel booking cancellations and we came to know that this is a major issue in many of the luxurious hotels.We also came up with a solution for this problem statement in our project.

What's next for ProfitForBrescia

We have used clever machine learning algorithms and predicted the accuracy score of above 0.95 for the dataset given.Further,we would also like to build and deploy a web application using flask or any other frameworks.It would be a great benefit for this Hotel and further like to have funding for our project from Brescia Norton Hotel

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