sklearn
.set_config¶
- sklearn.set_config(assume_finite=None, working_memory=None, print_changed_only=None, display=None, pairwise_dist_chunk_size=None, enable_cython_pairwise_dist=None)[source]¶
Set global scikit-learn configuration
New in version 0.19.
- Parameters:
- assume_finitebool, default=None
If True, validation for finiteness will be skipped, saving time, but leading to potential crashes. If False, validation for finiteness will be performed, avoiding error. Global default: False.
New in version 0.19.
- working_memoryint, default=None
If set, scikit-learn will attempt to limit the size of temporary arrays to this number of MiB (per job when parallelised), often saving both computation time and memory on expensive operations that can be performed in chunks. Global default: 1024.
New in version 0.20.
- print_changed_onlybool, default=None
If True, only the parameters that were set to non-default values will be printed when printing an estimator. For example,
print(SVC())
while True will only print ‘SVC()’ while the default behaviour would be to print ‘SVC(C=1.0, cache_size=200, …)’ with all the non-changed parameters.New in version 0.21.
- display{‘text’, ‘diagram’}, default=None
If ‘diagram’, estimators will be displayed as a diagram in a Jupyter lab or notebook context. If ‘text’, estimators will be displayed as text. Default is ‘diagram’.
New in version 0.23.
- pairwise_dist_chunk_sizeint, default=None
The number of row vectors per chunk for PairwiseDistancesReduction. Default is 256 (suitable for most of modern laptops’ caches and architectures).
Intended for easier benchmarking and testing of scikit-learn internals. End users are not expected to benefit from customizing this configuration setting.
New in version 1.1.
- enable_cython_pairwise_distbool, default=None
Use PairwiseDistancesReduction when possible. Default is True.
Intended for easier benchmarking and testing of scikit-learn internals. End users are not expected to benefit from customizing this configuration setting.
New in version 1.1.
See also
config_context
Context manager for global scikit-learn configuration.
get_config
Retrieve current values of the global configuration.
Examples using sklearn.set_config
¶
Release Highlights for scikit-learn 0.23
Compact estimator representations