prevision_quantum_nn.preprocessing.dimension_reduction.wrapper¶
wrapper module
Module Contents¶
Classes¶
Class Wrapper. |
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class
prevision_quantum_nn.preprocessing.dimension_reduction.wrapper.Wrapper¶ Class Wrapper.
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type_problem¶ can be either: classification, multiclassification or regression
- Type
str
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features_indexes¶ list of features indexes to be retained
- Type
list
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build(self, type_problem)¶ Builds the model.
- Parameters
type_problem (str) – type problem
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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
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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
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fit_transform(self, features, labels, num_components)¶ Fit and transforms the input features to the retained ones.
- Parameters
features (numpy array) – input features
labels (numpy array) – input labels
num_components (int) – number of components to scale the data
- Returns
- numpy array
output features
- Return type
features
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