Voting Classifier

Some of the docstrings for this module have been automatically extracted from the scikit-learn library and are covered by their respective licenses.

class node_ensemble.VotingClassifier

Uses voting to select answer from multiple classifiers. Add additional input ports for models by right-clicking on node and selecting “Create Input Port > models”

Configuration:

• names

  Comma separated list of model names, eg. Rescale, SVC

• copies

  Number of copies to make of each input model

• n_jobs

  The number of jobs to run in parallel for fit. If -1, then the number of jobs is set to the number of cores.

• voting

  If ‘hard’, uses predicted class labels for majority rule voting. Else if ‘soft’, predicts the class label based on the argmax of the sums of the predicted probabilities, which is recommended for an ensemble of well-calibrated classifiers.

Attributes:

• classes_

  The classes labels.

Inputs:

models : model

models

Outputs:

out-model : model

Output model