search

neurospin / pylearn-parsimony

Structured Machine Learning in Python
BSD 3-Clause "New" or "Revised" License
45 stars 16 forks source link

Compatibility with sklearn #12

Open duboism opened 8 years ago

duboism commented 8 years ago

Some properties of pylearn-parsimony Estimators are incompatible with sklearn Estimators. For instance in sklearn all parameters of the constructor have a default value (this allow to default construct the Estimator). There are many guidelines about the Estimator interface here (see chapters "APIs of scikit-learn objects" and "Rolling your own estimator"). Respecting this interface could help to mix parsimony and sklearn Estimators.

There are some tests in sklearn to ensure that all Estimators respect some assumptions of the API. One option to ensure the compatibility would be to use the same tests.

tomlof commented 7 years ago

Perhaps it's time to discuss this thoroughly? Being able to seamlessly cross over from scikit-learn to pylearn-parsimony and back would certainly be really useful!