- Sort Score
- Result 10 results
- Languages All
- Labels All
Results 821 - 830 of 1,826 for document (0.3 sec)
-
Robust vs Empirical covariance estimate — sciki...
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 — s...
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 -
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 -
Gaussian Mixture Model Sine Curve — scikit-lear...
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 -
Label Propagation digits active learning — scik...
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... -
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 -
fetch_species_distributions — scikit-learn 1.5....
Gallery examples: Species distribution modeling Kernel Density Estimate of Species Distributionsscikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_species_distributions.html -
load_sample_image — scikit-learn 1.5.2 document...
Gallery examples: Color Quantization using K-Meansscikit-learn.org/stable/modules/generated/sklearn.datasets.load_sample_image.html -
fetch_california_housing — scikit-learn 1.5.2 d...
Gallery examples: Release Highlights for scikit-learn 0.24 Comparing Random Forests and Histogram Gradient Boosting models Early stopping in Gradient Boosting Imputing missing values before buildin...scikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_california_housing.html -
sklearn.kernel_approximation — scikit-learn 1.5...
Approximate kernel feature maps based on Fourier transforms and count sketches. User guide. See the Kernel Approximation section for further details.scikit-learn.org/stable/api/sklearn.kernel_approximation.html