`prevision_quantum_nn.preprocessing.dimension_reduction.wrapper`¶

wrapper module

Module Contents¶

Wrapper Class Wrapper.

class prevision_quantum_nn.preprocessing.dimension_reduction.wrapper.Wrapper¶

Class Wrapper.

type_problem¶

can be either: classification, multiclassification or regression

Type:	str

features_indexes¶

list of features indexes to be retained

Type:	list

build(self, type_problem)¶

Builds the model.

Parameters:	type_problem (str) – type problem

fit(self, features, labels, num_components)¶

Fits observations.

Parameters:	features (numpy array) – input features labels (numpy array) – input labels num_components (int) – number of components to downscale the data to

transform(self, features)¶

Transforms the input features to the retained ones.

Parameters:	features (numpy array) – input features
Returns:	numpy array output features
Return type:	features

fit_transform(self, features, labels, num_components)¶

Fit and transforms the input features to the retained ones.

Parameters:

Returns:

Return type:

features