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  1. 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
    2025-11-15 10:03
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  2. 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
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  3. 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
    2025-11-15 10:03
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  4. 1.13. Feature selection — scikit-learn 1....

    The classes in the sklearn.feature_selection module can be used for feature selection/dimensionality reduction on sample sets, either to improve estimators’ accuracy scores or to boost their perfor...
    scikit-learn.org/stable/modules/feature_selection.html
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  5. 2.8. Density Estimation — scikit-learn 1....

    Density estimation walks the line between unsupervised learning, feature engineering, and data modeling. Some of the most popular and useful density estimation techniques are mixture models such as...
    scikit-learn.org/stable/modules/density.html
    2025-11-15 10:03
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  6. Plotting Cross-Validated Predictions — sc...

    This example shows how to use cross_val_predict together with PredictionErrorDisplay to visualize prediction errors. We will load the diabetes dataset and create an instance of a linear regression ...
    scikit-learn.org/stable/auto_examples/model_selection/plot_cv_predict.html
    2025-11-15 10:03
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  7. SGD: convex loss functions — scikit-learn...

    A plot that compares the various convex loss functions supported by SGDClassifier. Total running time of the script:(0 minutes 0.098 seconds) Launch binder Launch JupyterLite Download Jupyter noteb...
    scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_loss_functions.html
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  8. Agglomerative clustering with and without struc...

    This example shows the effect of imposing a connectivity graph to capture local structure in the data. The graph is simply the graph of 20 nearest neighbors. There are two advantages of imposing a ...
    scikit-learn.org/stable/auto_examples/cluster/plot_agglomerative_clustering.html
    2025-11-15 10:03
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  9. 1.10. Decision Trees — scikit-learn 1.7.2...

    Decision Trees (DTs) are a non-parametric supervised learning method used for classification and regression. The goal is to create a model that predicts the value of a target variable by learning s...
    scikit-learn.org/stable/modules/tree.html
    2025-11-15 10:03
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  10. 8.1. Toy datasets — scikit-learn 1.7.2 do...

    scikit-learn comes with a few small standard datasets that do not require to download any file from some external website. They can be loaded using the following functions: These datasets are usefu...
    scikit-learn.org/stable/datasets/toy_dataset.html
    2025-11-15 10:03
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