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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 -
Effect of model regularization on training and ...
In this example, we evaluate the impact of the regularization parameter in a linear model called ElasticNet. To carry out this evaluation, we use a validation curve using ValidationCurveDisplay. Th...scikit-learn.org/stable/auto_examples/model_selection/plot_train_error_vs_test_error.html -
2.9. Neural network models (unsupervised) — sci...
Restricted Boltzmann machines: Restricted Boltzmann machines (RBM) are unsupervised nonlinear feature learners based on a probabilistic model. The features extracted by an RBM or a hierarchy of RBM...scikit-learn.org/stable/modules/neural_networks_unsupervised.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 -
Normal, Ledoit-Wolf and OAS Linear Discriminant...
This example illustrates how the Ledoit-Wolf and Oracle Approximating Shrinkage (OAS) estimators of covariance can improve classification. Total running time of the script:(0 minutes 8.370 seconds)...scikit-learn.org/stable/auto_examples/classification/plot_lda.html -
Bisecting K-Means and Regular K-Means Performan...
This example shows differences between Regular K-Means algorithm and Bisecting K-Means. While K-Means clusterings are different when increasing n_clusters, Bisecting K-Means clustering builds on to...scikit-learn.org/stable/auto_examples/cluster/plot_bisect_kmeans.html -
Plot the decision surface of decision trees tra...
Plot the decision surface of a decision tree trained on pairs of features of the iris dataset. See decision tree for more information on the estimator. For each pair of iris features, the decision ...scikit-learn.org/stable/auto_examples/tree/plot_iris_dtc.html -
Manifold learning on handwritten digits: Locall...
We illustrate various embedding techniques on the digits dataset. Load digits dataset: We will load the digits dataset and only use six first of the ten available classes. We can plot the first hun...scikit-learn.org/stable/auto_examples/manifold/plot_lle_digits.html -
5.1. Partial Dependence and Individual Conditio...
Partial dependence plots (PDP) and individual conditional expectation (ICE) plots can be used to visualize and analyze interaction between the target response 1 and a set of input features of inter...scikit-learn.org/stable/modules/partial_dependence.html