summit.multiview_platform.multiview_classifiers.weighted_linear_early_fusion
weighted_linear_early_fusion¶
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classifier_class_name
= WeightedLinearEarlyFusion¶
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class
WeightedLinearEarlyFusion
(random_state=None, view_weights=None, monoview_classifier_name='decision_tree', monoview_classifier_config={})¶ Builds a monoview dataset by concatenating the views (with a weight if needed) and learns a monoview classifier on the concatenation
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set_params
(self, monoview_classifier_name='decision_tree', monoview_classifier_config={}, **params)¶
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get_params
(self, deep=True)¶
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fit
(self, X, y, train_indices=None, view_indices=None)¶
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predict
(self, X, sample_indices=None, view_indices=None)¶
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transform_data_to_monoview
(self, dataset, sample_indices, view_indices)¶ Here, we extract the data from the HDF5 dataset file and store all the concatenated views in one variable
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hdf5_to_monoview
(self, dataset, samples)¶ Here, we concatenate the views for the asked samples
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