https://github.com/machinalis/featureforge

A set of tools for creating and testing machine learning features, with a scikit-learn compatible API
https://github.com/machinalis/featureforge

Last synced: 7 months ago
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A set of tools for creating and testing machine learning features, with a scikit-learn compatible API

• Host: GitHub
• URL: https://github.com/machinalis/featureforge
• Owner: machinalis
• License: other
• Created: 2014-02-17T17:21:12.000Z (over 11 years ago)
• Default Branch: develop
• Last Pushed: 2017-12-26T17:08:12.000Z (almost 8 years ago)
• Last Synced: 2025-03-28T23:08:43.447Z (8 months ago)
• Language: Python
• Size: 184 KB
• Stars: 383
• Watchers: 33
• Forks: 77
• Open Issues: 11
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE

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README

          
Feature Forge

=============

This library provides a set of tools that can be useful in many machine

learning applications (classification, clustering, regression, etc.), and

particularly helpful if you use scikit-learn (although this can work if

you have a different algorithm).

Most machine learning problems involve an step of feature definition and

preprocessing. Feature Forge helps you with:

* Defining and documenting features

* Testing your features against specified cases and against randomly generated

  cases (stress-testing). This helps you making your application more robust

  against invalid/misformatted input data. This also helps you checking that

  low-relevance results when doing feature analysis is actually because the

  feature is bad, and not because there's a slight bug in your feature code.

* Evaluating your features on a data set, producing a feature evaluation

  matrix. The evaluator has a robust mode that allows you some tolerance both

  for invalid data and buggy features.

* Experimentation: running, registering, classifying and reproducing

  experiments for determining best settings for your problems.

Installation

------------

Just ``pip install featureforge``.

Documentation

-------------

Documentation is available at http://feature-forge.readthedocs.org/en/latest/

Contact information

-------------------

Feature Forge is copyright 2014 Machinalis (http://www.machinalis.com/). Its primary

authors are:

* Javier Mansilla  (jmansilla at github)

* Daniel Moisset  (dmoisset at github)

* Rafael Carrascosa  (rafacarrascosa at github)

Any contributions or suggestions are welcome, the official channel for this is

submitting github pull requests or issues.

Changelog

---------

0.1.7:

    - StatsManager api change (order of arguments swapped)

    - For experimentation, enabled a way of booking experiments forever.

0.1.6:

    - Bug fixes related to sparse matrices.

    - Small documentation improvements.

    - Reduced default logging verbosity.

0.1.5:

    - Using sparse numpy matrices by default.

0.1.4:

    - Discarded the need of using forked version of Schema library.

0.1.3:

    - Added support for running and generating stats for experiments

0.1.2:

    - Fixing installer dependencies

0.1.1:

    - Added support for python 3

    - Added support for bag-of-words features

0.1:

    - Initial release