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Pixel importances with a parallel forest of tre...
-1 means use all available cores. n_jobs = - 1 Load the...RandomForestClassifi(n_estimators=750, n_jobs=-1, random_state=42) In a Jupyter...scikit-learn.org/stable/auto_examples/ensemble/plot_forest_importances_faces.html -
all_estimators — scikit-learn 1.5.2 documentation
Skip to main content Back to top Ctrl + K GitHub all_estimators # sklearn.utils.discovery. all_estimators ( type_filt...scikit-learn.org/stable/modules/generated/sklearn.utils.discovery.all_estimators.html -
gen_batches — scikit-learn 1.5.2 documentation
Skip to main content Back to top Ctrl + K GitHub gen_batches # sklearn.utils. gen_batches ( n , batch_size , * , min_...scikit-learn.org/stable/modules/generated/sklearn.utils.gen_batches.html -
sklearn.multioutput — scikit-learn 1.5.2 docume...
Multioutput regression and classification. The estimators provided in this module are meta-estimators: they require a base estimator to be provided in their constructor. The meta-estimator extends ...scikit-learn.org/stable/api/sklearn.multioutput.html -
Pipelines and composite estimators — scikit-lea...
Examples of how to compose transformers and pipelines from other estimators. See the User Guide. Column Transformer with Heterogeneous Data Sources Column Transformer with Mixed Types Concatenating...scikit-learn.org/stable/auto_examples/compose/index.html -
sklearn.ensemble — scikit-learn 1.5.2 documenta...
Ensemble-based methods for classification, regression and anomaly detection. User guide. See the Ensembles: Gradient boosting, random forests, bagging, voting, stacking section for further details.scikit-learn.org/stable/api/sklearn.ensemble.html -
load_linnerud — scikit-learn 1.5.2 documentation
Skip to main content Back to top Ctrl + K GitHub load_linnerud # sklearn.datasets. load_linnerud ( * , return_X_y = F...scikit-learn.org/stable/modules/generated/sklearn.datasets.load_linnerud.html -
sklearn.covariance — scikit-learn 1.5.2 documen...
Methods and algorithms to robustly estimate covariance. They estimate the covariance of features at given sets of points, as well as the precision matrix defined as the inverse of the covariance. C...scikit-learn.org/stable/api/sklearn.covariance.html -
sklearn.inspection — scikit-learn 1.5.2 documen...
Tools for model inspection. User guide. See the Inspection section for further details. Plotting:scikit-learn.org/stable/api/sklearn.inspection.html -
sklearn.manifold — scikit-learn 1.5.2 documenta...
Data embedding techniques. User guide. See the Manifold learning section for further details.scikit-learn.org/stable/api/sklearn.manifold.html