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Plot multi-class SGD on the iris dataset — scik...
Plot decision surface of multi-class SGD on iris dataset. The hyperplanes corresponding to the three one-versus-all (OVA) classifiers are represented by the dashed lines. Total running time of the ...scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_iris.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 -
One-class SVM with non-linear kernel (RBF) — sc...
An example using a one-class SVM for novelty detection. One-class SVM is an unsupervised algorithm that learns a decision function for novelty detection: classifying new data as similar or differen...scikit-learn.org/stable/auto_examples/svm/plot_oneclass.html -
3.1. Cross-validation: evaluating estimator per...
Learning the parameters of a prediction function and testing it on the same data is a methodological mistake: a model that would just repeat the labels of the samples that it has just seen would ha...scikit-learn.org/stable/modules/cross_validation.html -
A demo of structured Ward hierarchical clusteri...
Compute the segmentation of a 2D image with Ward hierarchical clustering. The clustering is spatially constrained in order for each segmented region to be in one piece. Generate data: Resize it to ...scikit-learn.org/stable/auto_examples/cluster/plot_coin_ward_segmentation.html -
Hashing feature transformation using Totally Ra...
RandomTreesEmbedding provides a way to map data to a very high-dimensional, sparse representation, which might be beneficial for classification. The mapping is completely unsupervised and very effi...scikit-learn.org/stable/auto_examples/ensemble/plot_random_forest_embedding.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 -
Lasso model selection: AIC-BIC / cross-validati...
This example focuses on model selection for Lasso models that are linear models with an L1 penalty for regression problems. Indeed, several strategies can be used to select the value of the regular...scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_model_selection.html -
Comparing randomized search and grid search for...
Compare randomized search and grid search for optimizing hyperparameters of a linear SVM with SGD training. All parameters that influence the learning are searched simultaneously (except for the nu...scikit-learn.org/stable/auto_examples/model_selection/plot_randomized_search.html