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”
Documentation¶
Attributes¶
- classes_
The classes labels.
Definition¶
Input ports¶
- models 1 - inf, model
models
Output ports¶
- out-model model
Output model
Configuration¶
- Copies (copies)
Number of copies to make of each input model
- Number of jobs (n_jobs)
The number of jobs to run in parallel for
fit
.None
means 1 unless in ajoblib.parallel_backend
context.-1
means using all processors. See n_jobs for more details.Added in version 0.18.
- Estimators (names)
Comma separated list of model names, eg. Rescale, SVC
- Voting (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.
Implementation¶
- class node_ensemble.VotingClassifier[source]