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Backbones for parameterized models.

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Backbones for parameterized models.

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Spines was built to provide a skeleton for Model classes: a common interface for users to build models around (with some tools and utilities which take advantage of those commonalities). It's core Model class is similar, in structure, to some of scikit-learn's underlying Estimator classes - but with a single set of unified functions for all models, namely:

  • Build
  • Fit
  • Predict
  • Score
  • Error

The predict method is the only one that's required to be implemented, though the others are likely useful most of the time (and often required to take advantage of some of the additional utilities provided by spines).

Spines also incorporates automatic version management for your models - something akin to a very lightweight git - but for individual models. It also caches results generated during various iterations of the development/fitting process so that they're not lost during - something that can (and often does) happen during very iterative model development work.


To install spines use your package manager of choice, an example using pipenv would be:

$ pipenv install spines


The latest documentation is hosted on read the docs.


This project is licensed under the MIT License, for more information see the LICENSE file.

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