- Sort Score
- Num 10 results
- Language All
- Labels All
Results 181 - 190 of 4,138 for document (3.98 seconds)
Filter
-
Ensemble methods — scikit-learn 1.8.0 documenta...
Examples concerning the sklearn.ensemble module. Categorical Feature Support in Gradient Boosting Combine predictors using stacking Comparing Random Forests and Histogram Gradient Boosting models C...scikit-learn.org/stable/auto_examples/ensemble/index.html -
Feature Selection — scikit-learn 1.8.0 document...
Examples concerning the sklearn.feature_selection module. Comparison of F-test and mutual information Model-based and sequential feature selection Pipeline ANOVA SVM Recursive feature elimination R...scikit-learn.org/stable/auto_examples/feature_selection/index.html -
Multioutput methods — scikit-learn 1.8.0 docume...
Examples concerning the sklearn.multioutput module. Multilabel classification using a classifier chainscikit-learn.org/stable/auto_examples/multioutput/index.html -
SGD: Penalties — scikit-learn 1.8.0 documentation
Contours of where the penalty is equal to 1 for the three penalties L1, L2 and elastic-net. All of the above are supported by SGDClassifier and SGDRegressor. Total running time of the script:(0 min...scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_penalties.html -
Multiclass methods — scikit-learn 1.8.0 documen...
Examples concerning the sklearn.multiclass module. Overview of multiclass training meta-estimatorsscikit-learn.org/stable/auto_examples/multiclass/index.html -
sklearn.ensemble — scikit-learn 1.8.0 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 -
sklearn.multioutput — scikit-learn 1.8.0 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 -
sklearn.pipeline — scikit-learn 1.8.0 documenta...
Utilities to build a composite estimator as a chain of transforms and estimators. User guide. See the Pipelines and composite estimators section for further details.scikit-learn.org/stable/api/sklearn.pipeline.html -
sklearn.inspection — scikit-learn 1.8.0 documen...
Tools for model inspection. User guide. See the Inspection section for further details. Plotting:scikit-learn.org/stable/api/sklearn.inspection.html -
sklearn.covariance — scikit-learn 1.8.0 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