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