https://github.com/parv-bhargava/air-score
Data analysis and prediction on airline customer satisfaction
https://github.com/parv-bhargava/air-score
airline-satisfaction decision-trees exploratory-data-analysis linear-regression logistic-regression r
Last synced: 10 months ago
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Data analysis and prediction on airline customer satisfaction
- Host: GitHub
- URL: https://github.com/parv-bhargava/air-score
- Owner: parv-bhargava
- Created: 2023-10-07T16:07:05.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-01-11T23:07:16.000Z (over 2 years ago)
- Last Synced: 2025-02-14T01:17:42.389Z (over 1 year ago)
- Topics: airline-satisfaction, decision-trees, exploratory-data-analysis, linear-regression, logistic-regression, r
- Language: HTML
- Homepage: https://parv-bhargava.github.io/air-score/
- Size: 103 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# [AirScore](https://parv-bhargava.github.io/air-score/)
## Problem Statement:
Airline passengers satisfaction is a critical metric that significantly influences an airline's success in today's competitive travel industry. Understanding the factors that contribute to passengers satisfaction is essential for airlines to improve their services, enhance customer experiences, and maintain a strong market position. Therefore, the goal of this research is to identify and analyze the various factors that can be used to predict airline passengers satisfaction
[Dataset](https://www.kaggle.com/datasets/teejmahal20/airline-passenger-satisfaction?select=train.csv)