summit.multiview_platform.multiview_classifiers.svm_jumbo_fusion

svm_jumbo_fusion

classifier_class_name = 'SVMJumboFusion'
class SVMJumboFusion(random_state=None, classifiers_names=None, classifier_configs=None, nb_cores=1, weights=None, nb_monoview_per_view=1, C=1.0, kernel='rbf', degree=2, rs=None)

This classifier learns monoview classifiers on each view and then uses an SVM on their decisions to aggregate them.

need_probas = False
aggregation_estimator
C = 1.0
kernel = 'rbf'
degree = 2
set_params(C=1.0, kernel='rbf', degree=1, **params)

Set the parameters of this estimator.

The method works on simple estimators as well as on nested objects (such as Pipeline). The latter have parameters of the form <component>__<parameter> so that it’s possible to update each component of a nested object.

Parameters:

**params (dict) – Estimator parameters.

Returns:

self – Estimator instance.

Return type:

estimator instance