simpleml.transformers

Base Module for Transformers

Use Mixin class for expected methods in multiple inheritance subclasses. Use Base class for other ones

Subpackages

• simpleml.transformers.fitful_transformers
• simpleml.transformers.fitless_transformers

Submodules

• simpleml.transformers.base_transformer

Package Contents

Classes

Transformer	Base Transformer class with param management - Can interfere with mro
TransformerMixin	Base Transformer class that implements all the necessary methods

simpleml.transformers.__author__ = Elisha Yadgaran

class simpleml.transformers.Transformer(**kwargs)

Bases: simpleml.transformers.base_transformer.TransformerMixin

Base Transformer class with param management - Can interfere with mro if used as a mixin - Use TransformerMixin in that case

Assumes only seeding kwargs passed - will affect hash otherwise if random unused parameters are passed

get(self, param)

get_params(self, **kwargs)

Should only return seeding parameters, not fit ones (ie params of unfit object should be identical to fit object)

set_params(self, **kwargs)

class simpleml.transformers.TransformerMixin

Bases: sklearn.base.TransformerMixin

Base Transformer class that implements all the necessary methods

Default behavior is to do nothing - overwrite later

object_type = TRANSFORMER

fit(self, X, y=None, **kwargs)

get_feature_names(self, input_feature_names)

get_params(self, **kwargs)

Should only return seeding parameters, not fit ones (ie params of unfit object should be identical to fit object)

set_params(self, **kwargs)

transform(self, X, y=None, **kwargs)