Multi-output regressor¶
Fits one regressor for each target of outputs. Useful for extending regressors that do not natively support multiple outputs
Configuration:
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.When individual estimators are fast to train or predict using n_jobs>1 can result in slower performance due to the overhead of spawning processes.
Attributes:
- Input ports:
- model : model
- model
- Output ports:
- out-model : model
- Output model
- n_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.When individual estimators are fast to train or predict using n_jobs>1 can result in slower performance due to the overhead of spawning processes.
Some of the docstrings for this module have been automatically extracted from the scikit-learn library and are covered by their respective licenses.