- Sort Score
- Result 10 results
- Languages All
- Labels All
Results 1231 - 1240 of 1,826 for document (0.07 sec)
-
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 -
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 -
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 -
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 -
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 -
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 -
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 -
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 -
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 -
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