Skip to main content

A Python library to conjugate verbs using Machine Learning techiques.

Project description

MLConjug

Pypi Python Package Index Status Linux Continuous Integration Status Windows Continuous Integration Status Documentation Status Depedencies Update Status Coverage Status

A Python library to conjugate verbs of Romance languages using Machine Learning techniques. Any verb in one of the supported language can be conjugated as the module contains a Machine Learning model of how romance verbs behave. Even completely new or made-up verbs can be successfully conjugated in this manner. The supplied pre-trained models are composed of:

  • a binary feature extractor,

  • a feature selector using Linear Support Vector Classification,

  • a classifier using Stochastic Gradient Descent.

MLConjug uses scikit-learn to implement the Machine Learning algorithms. Users of the library can use any compatible classifiers from scikit-learn to modify and retrain the model.

The training data is based on Verbiste https://perso.b2b2c.ca/~sarrazip/dev/verbiste.html .

Supported Languages

  • French

  • Spanish (coming in next update)

  • Italian (coming in next update)

  • Portuguese (coming in next update)

Features

  • Easy to use API.

  • Includes a pre-trained model with 99.53% accuracy in predicting conjugation class of unknown verbs.

  • Easily train new models or add new romance language.

  • Easily integrate MLConjug in your own projects.

  • Can be used as a command line tool.

Credits

This package was created with the help of Verbiste and scikit-learn.

History

1.0.0 (2018-06-10)

  • First release on PyPI.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mlconjug-1.0.0.tar.gz (22.8 kB view hashes)

Uploaded Source

Built Distribution

mlconjug-1.0.0-py2.py3-none-any.whl (7.8 kB view hashes)

Uploaded Python 2 Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page