https://github.com/joshjetson/taxi_tip_prediction

A machine learning model which can predict the amount of gratuity a taxi driver may receive
https://github.com/joshjetson/taxi_tip_prediction

Last synced: 6 days ago
JSON representation

A machine learning model which can predict the amount of gratuity a taxi driver may receive

• Host: GitHub
• URL: https://github.com/joshjetson/taxi_tip_prediction
• Owner: joshjetson
• Created: 2023-03-16T21:15:38.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2023-03-17T03:25:42.000Z (almost 2 years ago)
• Last Synced: 2024-11-07T17:55:51.491Z (about 2 months ago)
• Language: Python
• Size: 4.88 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# ![Taxi Tip Prediction Model](https://i.imgur.com/maWyDKI.jpeg)

This is a predictive model that can predict, with a high measure of accuracy, what a given tip might be based on real data from previous taxi trips.

## Data

## [Data](https://www.kaggle.com/datasets/microize/newyork-yellow-taxi-trip-data-2020-2019?select=yellow_tripdata_2019-06.csv)

The data in this model is sourced from real taxi rides and is provided by the yellow cab company via kaggle.

## Main Concept

Based on independent variables such as:

- Driver ID

- Total trip cost

- Pick up location

- Drop off location

- Payment type

- Pickup time

- Drop off time

Can we determine what a new rider might tip for a taxi ride?

## Use cases

This code can be used to apply these same methods on another similar data set in an aim to predict what a specific value might be based on a number of different independent variables.

## [Usage](https://colab.research.google.com/) 

- Anyone could use google Colaboratory to use this code and modify it to their data needs.

### Development

Want to contribute? Great!

To fix a bug or enhance an existing module, follow these steps:

- Fork the repo

- Create a new branch (`git checkout -b improve-feature`)

- Make the appropriate changes in the files

- Add changes to reflect the changes made

- Commit your changes (`git commit -am 'Improve feature'`)

- Push to the branch (`git push origin improve-feature`)

- Create a Pull Request 

### Bug / Feature Request

If you find a bug in this code please let me know.

## Built with 

- [Scikit-Learn](https://scikit-learn.org/) - For their models and tools

- [Python](https://www.python.org/) - For its flexibility and abundant amount of resources

- [Numpy](https://numpy.org/) - For computation

- [Pandas](https://pandas.pydata.org/) - For organization, processing and data visualization

- [Matplotlib](https://matplotlib.org/) - For data visualization

- [Snapml](https://www.zurich.ibm.com/snapml/) For their decision tree model regressor

## To-do

- Build an accompanying gui or webapp as to make this an actual application anyone can use.

- Create more data visualizations