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TruncatedSVD — scikit-learn 1.8.0 documentation
text documents using k-means Clustering text documents using...scikit-learn.org/stable/modules/generated/sklearn.decomposition.TruncatedSVD.html -
A demo of the mean-shift clustering algorithm —...
Reference: Dorin Comaniciu and Peter Meer, “Mean Shift: A robust approach toward feature space analysis”. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2002. pp. 603-619. Generate...scikit-learn.org/stable/auto_examples/cluster/plot_mean_shift.html -
Ledoit-Wolf vs OAS estimation — scikit-learn 1....
The usual covariance maximum likelihood estimate can be regularized using shrinkage. Ledoit and Wolf proposed a close formula to compute the asymptotically optimal shrinkage parameter (minimizing a...scikit-learn.org/stable/auto_examples/covariance/plot_lw_vs_oas.html -
L1-based models for Sparse Signals — scikit-lea...
The present example compares three l1-based regression models on a synthetic signal obtained from sparse and correlated features that are further corrupted with additive Gaussian noise: a Lasso;, a...scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_and_elasticnet.html -
Curve Fitting with Bayesian Ridge Regression — ...
Computes a Bayesian Ridge Regression of Sinusoids. See Bayesian Ridge Regression for more information on the regressor. In general, when fitting a curve with a polynomial by Bayesian ridge regressi...scikit-learn.org/stable/auto_examples/linear_model/plot_bayesian_ridge_curvefit.html -
Ridge coefficients as a function of the L2 Regu...
A model that overfits learns the training data too well, capturing both the underlying patterns and the noise in the data. However, when applied to unseen data, the learned associations may not hol...scikit-learn.org/stable/auto_examples/linear_model/plot_ridge_coeffs.html -
Model-based and sequential feature selection — ...
This example illustrates and compares two approaches for feature selection: SelectFromModel which is based on feature importance, and SequentialFeatureSelector which relies on a greedy approach. We...scikit-learn.org/stable/auto_examples/feature_selection/plot_select_from_model_diabetes.html -
Gaussian processes on discrete data structures ...
This example illustrates the use of Gaussian processes for regression and classification tasks on data that are not in fixed-length feature vector form. This is achieved through the use of kernel f...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpr_on_structured_data.html -
Ordinary Least Squares and Ridge Regression — s...
Ordinary Least Squares: We illustrate how to use the ordinary least squares (OLS) model, LinearRegression, on a single feature of the diabetes dataset. We train on a subset of the data, evaluate on...scikit-learn.org/stable/auto_examples/linear_model/plot_ols_ridge.html -
Detection error tradeoff (DET) curve — scikit-l...
In this example, we compare two binary classification multi-threshold metrics: the Receiver Operating Characteristic (ROC) and the Detection Error Tradeoff (DET). For such purpose, we evaluate two ...scikit-learn.org/stable/auto_examples/model_selection/plot_det.html