https://github.com/v-adhithyan/gender-guess-indiannames

Guess gender from indian names.
https://github.com/v-adhithyan/gender-guess-indiannames

gender-classification gender-classifier gender-from-name gender-prediction machine naive-bayes-classifier nltk nltk-python python3

Last synced: 18 days ago
JSON representation

Guess gender from indian names.

• Host: GitHub
• URL: https://github.com/v-adhithyan/gender-guess-indiannames
• Owner: v-adhithyan
• License: mit
• Created: 2019-01-18T06:42:59.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2022-01-21T19:47:38.000Z (almost 3 years ago)
• Last Synced: 2024-11-30T16:44:08.243Z (about 2 months ago)
• Topics: gender-classification, gender-classifier, gender-from-name, gender-prediction, machine, naive-bayes-classifier, nltk, nltk-python, python3
• Language: Python
• Homepage: https://pypi.org/project/guess-indian-gender/
• Size: 156 KB
• Stars: 10
• Watchers: 2
• Forks: 8
• Open Issues: 5
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# Guess gender from indian names

## Motivation

I was not able to find a open source library that guess

gender from indian names. So made one.

## Prerequisites

- Python 3.7

- Pipenv

## Development - Setup instructions

- Clone this repository.

- cd to the repo

- Activate pipenv `pipenv shell`

- Install dependencies `pipenv install`

- Fire up a python shell and type the following.

```python

>>> from guess_indian_gender import IndianGenderPredictor

>>> i = IndianGenderPredictor()

>>> i.predict(name="adhi") # returns male

```

## Installation

- `pip install guess-indian-gender`

## Accuracy

- Currently the accuracy is 0.88. Any contributions are welcome

to improve the accuracy.

## Changelog

- When the last letter is considered as a feature for gender detection

the accuracy is 78%.

- When the last four letters was considered the accuracy became 88%.

## Todo

- [x] Convert to Pip package.

- [x] Convert to nice oops.

- [ ] Improve accuracy to 95%.

## Dataset credits

- 

- Male names - 

- Female names - 

## License

MIT. See license file for more info