Voting Classifier¶
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: |
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Attributes: |
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Inputs: |
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Outputs: |
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Ports:
Inputs:
models: model
models
Outputs:
out-model: model
Output model
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.
Some of the docstrings for this module have been automatically extracted from the scikit-learn library and are covered by their respective licenses.