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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 -
__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 -
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 -
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 0.135 seconds) Launch binder Launch JupyterLite ...scikit-learn.org/stable/auto_examples/neighbors/plot_nearest_centroid.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 -
Pipelines and composite estimators — scik...
Examples of how to compose transformers and pipelines from other estimators. See the User Guide. Column Transformer with Heterogeneous Data Sources Column Transformer with Mixed Types Concatenating...scikit-learn.org/stable/auto_examples/compose/index.html -
7.7. Kernel Approximation — scikit-learn ...
This submodule contains functions that approximate the feature mappings that correspond to certain kernels, as they are used for example in support vector machines (see Support Vector Machines). Th...scikit-learn.org/stable/modules/kernel_approximation.html -
1.8. Cross decomposition — scikit-learn 1...
The cross decomposition module contains supervised estimators for dimensionality reduction and regression, belonging to the “Partial Least Squares” family. Cross decomposition algorithms find the f...scikit-learn.org/stable/modules/cross_decomposition.html -
1.15. Isotonic regression — scikit-learn ...
The class IsotonicRegression fits a non-decreasing real function to 1-dimensional data. It solves the following problem:\min \sum_i w_i (y_i - \hat{y}_i)^2 subject to\hat{y}_i \le \hat{y}_j wheneve...scikit-learn.org/stable/modules/isotonic.html -
Plot Hierarchical Clustering Dendrogram —...
This example plots the corresponding dendrogram of a hierarchical clustering using AgglomerativeClustering and the dendrogram method available in scipy. Total running time of the script:(0 minutes ...scikit-learn.org/stable/auto_examples/cluster/plot_agglomerative_dendrogram.html