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SVM: Maximum margin separating hyperplane — sci...
Plot the maximum margin separating hyperplane within a two-class separable dataset using a Support Vector Machine classifier with linear kernel. Total running time of the script:(0 minutes 0.053 se...scikit-learn.org/stable/auto_examples/svm/plot_separating_hyperplane.html -
7.4. Imputation of missing values — scikit-lear...
For various reasons, many real world datasets contain missing values, often encoded as blanks, NaNs or other placeholders. Such datasets however are incompatible with scikit-learn estimators which ...scikit-learn.org/stable/modules/impute.html -
1.3. Kernel ridge regression — scikit-learn 1.8...
Kernel ridge regression (KRR)[M2012] combines Ridge regression and classification(linear least squares with L_2-norm regularization) with the kernel trick. It thus learns a linear function in the s...scikit-learn.org/stable/modules/kernel_ridge.html -
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 -
Multi-class AdaBoosted Decision Trees — scikit-...
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 — 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 -
Set up your development environment — scikit-le...
Fork the scikit-learn repository: First, you need to create an account on GitHub (if you do not already have one) and fork the project repository by clicking on the ‘Fork’ button near the top of th...scikit-learn.org/stable/developers/development_setup.html -
Features in Histogram Gradient Boosting Trees —...
Histogram-Based Gradient Boosting(HGBT) models may be one of the most useful supervised learning models in scikit-learn. They are based on a modern gradient boosting implementation comparable to Li...scikit-learn.org/stable/auto_examples/ensemble/plot_hgbt_regression.html