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1.16. Probability calibration — scikit-le...
When performing classification you often want not only to predict the class label, but also obtain a probability of the respective label. This probability gives you some kind of confidence on the p...scikit-learn.org/stable/modules/calibration.html -
8.1. Toy datasets — scikit-learn 1.8.0 do...
scikit-learn comes with a few small standard datasets that do not require to download any file from some external website. They can be loaded using the following functions: These datasets are usefu...scikit-learn.org/stable/datasets/toy_dataset.html -
Prediction Intervals for Gradient Boosting Regr...
This example shows how quantile regression can be used to create prediction intervals. See Features in Histogram Gradient Boosting Trees for an example showcasing some other features of HistGradien...scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_quantile.html -
Robust vs Empirical covariance estimate —...
The usual covariance maximum likelihood estimate is very sensitive to the presence of outliers in the data set. In such a case, it would be better to use a robust estimator of covariance to guarant...scikit-learn.org/stable/auto_examples/covariance/plot_robust_vs_empirical_covariance.html -
Lagged features for time series forecasting ...
This example demonstrates how Polars-engineered lagged features can be used for time series forecasting with HistGradientBoostingRegressor on the Bike Sharing Demand dataset. See the example on Tim...scikit-learn.org/stable/auto_examples/applications/plot_time_series_lagged_features.html -
Multi-class AdaBoosted Decision Trees — s...
This example shows how boosting can improve the prediction accuracy on a multi-label classification problem. It reproduces a similar experiment as depicted by Figure 1 in Zhu et al 1. The core prin...scikit-learn.org/stable/auto_examples/ensemble/plot_adaboost_multiclass.html -
Gaussian Mixture Model Sine Curve — sciki...
This example demonstrates the behavior of Gaussian mixture models fit on data that was not sampled from a mixture of Gaussian random variables. The dataset is formed by 100 points loosely spaced fo...scikit-learn.org/stable/auto_examples/mixture/plot_gmm_sin.html -
Imputing missing values with variants of Iterat...
The IterativeImputer class is very flexible - it can be used with a variety of estimators to do round-robin regression, treating every variable as an output in turn. In this example we compare some...scikit-learn.org/stable/auto_examples/impute/plot_iterative_imputer_variants_comparison.html -
Overview of multiclass training meta-estimators...
In this example, we discuss the problem of classification when the target variable is composed of more than two classes. This is called multiclass classification. In scikit-learn, all estimators su...scikit-learn.org/stable/auto_examples/multiclass/plot_multiclass_overview.html -
Label Propagation digits: Active learning ̵...
Demonstrates an active learning technique to learn handwritten digits using label propagation. We start by training a label propagation model with only 10 labeled points, then we select the top fiv...scikit-learn.org/stable/auto_examples/semi_supervised/plot_label_propagation_digits_active_learni...