https://github.com/jimmymugendi/british-airways-virtual-internship-task2

This GitHub repository for the British Airways project contains code and resources related to analyzing customer booking behavior with British Airways. It includes data preprocessing, exploratory data analysis, model training using the XGBoost classifier, and evaluation of the model's performance.
https://github.com/jimmymugendi/british-airways-virtual-internship-task2

machine-learning pandas performance-metrics random-forest-classifier skit-learn xgboost-classifier

Last synced: about 7 hours ago
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This GitHub repository for the British Airways project contains code and resources related to analyzing customer booking behavior with British Airways. It includes data preprocessing, exploratory data analysis, model training using the XGBoost classifier, and evaluation of the model's performance.

• Host: GitHub
• URL: https://github.com/jimmymugendi/british-airways-virtual-internship-task2
• Owner: Jimmymugendi
• Created: 2024-04-09T15:07:25.000Z (7 months ago)
• Default Branch: main
• Last Pushed: 2024-04-09T15:18:14.000Z (7 months ago)
• Last Synced: 2024-04-09T19:15:58.658Z (7 months ago)
• Topics: machine-learning, pandas, performance-metrics, random-forest-classifier, skit-learn, xgboost-classifier
• Language: Jupyter Notebook
• Homepage:
• Size: 755 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# British Airways Project

# This project aims to analyze customer booking behavior with British Airways.

Description

The dataset contains information about customer booking details, flight information, etc. The goal of the project is to predict customer booking behavior and understand the factors influencing booking decisions.

## Tools Used

- Python

- Pandas

- Scikit-learn

- XGBoost

- GitHub

## Dataset

The dataset used in this project contains booking details, flight information, etc.

## Task Two: XGBoost Classification

In this part of the project, we used XGBoost for classification to predict whether a customer will book a flight with British Airways.

We performed data preprocessing, model training, and evaluation using the XGBoost classifier.

# Results

The XGBoost classification model achieved an accuracy of 84.94% on the validation set.