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Language Optimization | App Search documentatio...
« Indexing Documents Guide Log settings guide »...Optimization IMPORTANT : This documentation is no longer updated. Refer...www.elastic.co/guide/en/app-search/8.19/language-optimization-guide.html -
2. Unsupervised learning — scikit-learn 1...
Gaussian mixture models- Gaussian Mixture, Variational Bayesian Gaussian Mixture., Manifold learning- Introduction, Isomap, Locally Linear Embedding, Modified Locally Linear Embedding, Hessian Eige...scikit-learn.org/stable/unsupervised_learning.html -
Theil-Sen Regression — scikit-learn 1.7.2...
Computes a Theil-Sen Regression on a synthetic dataset. See Theil-Sen estimator: generalized-median-based estimator for more information on the regressor. Compared to the OLS (ordinary least square...scikit-learn.org/stable/auto_examples/linear_model/plot_theilsen.html -
Polynomial and Spline interpolation — sci...
This example demonstrates how to approximate a function with polynomials up to degree degree by using ridge regression. We show two different ways given n_samples of 1d points x_i: PolynomialFeatur...scikit-learn.org/stable/auto_examples/linear_model/plot_polynomial_interpolation.html -
Gradient Boosting regression — scikit-lea...
This example demonstrates Gradient Boosting to produce a predictive model from an ensemble of weak predictive models. Gradient boosting can be used for regression and classification problems. Here,...scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_regression.html -
__sklearn_is_fitted__ as Developer API — ...
The__sklearn_is_fitted__ method is a convention used in scikit-learn for checking whether an estimator object has been fitted or not. This method is typically implemented in custom estimator classe...scikit-learn.org/stable/auto_examples/developing_estimators/sklearn_is_fitted.html -
Generalized Linear Models — scikit-learn ...
Examples concerning the sklearn.linear_model module. Comparing Linear Bayesian Regressors Curve Fitting with Bayesian Ridge Regression Decision Boundaries of Multinomial and One-vs-Rest Logistic Re...scikit-learn.org/stable/auto_examples/linear_model/index.html -
Recursive feature elimination — scikit-le...
This example demonstrates how Recursive Feature Elimination ( RFE) can be used to determine the importance of individual pixels for classifying handwritten digits. RFE recursively removes the least...scikit-learn.org/stable/auto_examples/feature_selection/plot_rfe_digits.html -
Importance of Feature Scaling — scikit-le...
Feature scaling through standardization, also called Z-score normalization, is an important preprocessing step for many machine learning algorithms. It involves rescaling each feature such that it ...scikit-learn.org/stable/auto_examples/preprocessing/plot_scaling_importance.html -
Nearest Centroid Classification — scikit-...
Sample usage of Nearest Centroid classification. It will plot the decision boundaries for each class.,., Total running time of the script:(0 minutes 0.173 seconds) Launch binder Launch JupyterLite ...scikit-learn.org/stable/auto_examples/neighbors/plot_nearest_centroid.html