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  1. Receiver Operating Characteristic (ROC) with cr...

    This example presents how to estimate and visualize the variance of the Receiver Operating Characteristic (ROC) metric using cross-validation. ROC curves typically feature true positive rate (TPR) ...
    scikit-learn.org/stable/auto_examples/model_selection/plot_roc_crossval.html
    Sat Nov 23 04:49:15 UTC 2024
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  2. sort_graph_by_row_values — scikit-learn 1.5.2 d...

    Skip to main content Back to top Ctrl + K GitHub sort_graph_by_row_values # sklearn.neighbors. sort_graph_by_row_valu...
    scikit-learn.org/stable/modules/generated/sklearn.neighbors.sort_graph_by_row_values.html
    Sat Nov 23 04:49:15 UTC 2024
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  3. 1.14. Semi-supervised learning — scikit-learn 1...

    Semi-supervised learning is a situation in which in your training data some of the samples are not labeled. The semi-supervised estimators in sklearn.semi_supervised are able to make use of this ad...
    scikit-learn.org/stable/modules/semi_supervised.html
    Fri Nov 22 23:53:26 UTC 2024
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  4. 1.2. Linear and Quadratic Discriminant Analysis...

    Linear Discriminant Analysis ( LinearDiscriminantAnalysis) and Quadratic Discriminant Analysis ( QuadraticDiscriminantAnalysis) are two classic classifiers, with, as their names suggest, a linear a...
    scikit-learn.org/stable/modules/lda_qda.html
    Fri Nov 22 23:53:26 UTC 2024
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  5. Comparing random forests and the multi-output m...

    An example to compare multi-output regression with random forest and the multioutput.MultiOutputRegressor meta-estimator. This example illustrates the use of the multioutput.MultiOutputRegressor me...
    scikit-learn.org/stable/auto_examples/ensemble/plot_random_forest_regression_multioutput.html
    Sat Nov 23 04:49:14 UTC 2024
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  6. Novelty detection with Local Outlier Factor (LO...

    The Local Outlier Factor (LOF) algorithm is an unsupervised anomaly detection method which computes the local density deviation of a given data point with respect to its neighbors. It considers as ...
    scikit-learn.org/stable/auto_examples/neighbors/plot_lof_novelty_detection.html
    Sat Nov 23 04:49:15 UTC 2024
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  7. Visualizing cross-validation behavior in scikit...

    Choosing the right cross-validation object is a crucial part of fitting a model properly. There are many ways to split data into training and test sets in order to avoid model overfitting, to stand...
    scikit-learn.org/stable/auto_examples/model_selection/plot_cv_indices.html
    Sat Nov 23 04:49:16 UTC 2024
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  8. Comparing anomaly detection algorithms for outl...

    This example shows characteristics of different anomaly detection algorithms on 2D datasets. Datasets contain one or two modes (regions of high density) to illustrate the ability of algorithms to c...
    scikit-learn.org/stable/auto_examples/miscellaneous/plot_anomaly_comparison.html
    Sat Nov 23 04:49:14 UTC 2024
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  9. Gaussian process classification (GPC) on iris d...

    This example illustrates the predicted probability of GPC for an isotropic and anisotropic RBF kernel on a two-dimensional version for the iris-dataset. The anisotropic RBF kernel obtains slightly ...
    scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpc_iris.html
    Sat Nov 23 04:49:15 UTC 2024
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  10. Concentration Prior Type Analysis of Variation ...

    This example plots the ellipsoids obtained from a toy dataset (mixture of three Gaussians) fitted by the BayesianGaussianMixture class models with a Dirichlet distribution prior ( weight_concentrat...
    scikit-learn.org/stable/auto_examples/mixture/plot_concentration_prior.html
    Sat Nov 23 04:49:15 UTC 2024
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