miml.classifier.mi.mi_wrapper_classifier.MIWrapperClassifier#
- class miml.classifier.mi.mi_wrapper_classifier.MIWrapperClassifier(base_classifier=DecisionTreeClassifier())#
MIWrapper Classifier.
A simple Wrapper method for applying standard propositional learners to multi-instance data.
Attributes#
- base_classifier
Classifier to be used
References#
E. T. Frank, X. Xu (2003). Applying propositional learning algorithms to multi-instance data. Department of Computer Science, University of Waikato, Hamilton, NZ.
- __init__(base_classifier=DecisionTreeClassifier())#
Methods
__init__
([base_classifier])fit
(x_train, y_train[, weight])Fit the classifier to the training data.
predict
(bag)Predict the label of the bag
predict_proba
(x_test)Predict probabilities of given data of having a positive label