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Feature agglomeration vs. univariate selection ...
This example compares 2 dimensionality reduction strategies: univariate feature selection with Anova, feature agglomeration with Ward hierarchical clustering. Both methods are compared in a regress...scikit-learn.org/stable/auto_examples/cluster/plot_feature_agglomeration_vs_univariate_selection.... -
1.4. Support Vector Machines — scikit-lea...
Support vector machines (SVMs) are a set of supervised learning methods used for classification, regression and outliers detection. The advantages of support vector machines are: Effective in high ...scikit-learn.org/stable/modules/svm.html -
L1 Penalty and Sparsity in Logistic Regression ...
Comparison of the sparsity (percentage of zero coefficients) of solutions when L1, L2 and Elastic-Net penalty are used for different values of C. We can see that large values of C give more freedom...scikit-learn.org/stable/auto_examples/linear_model/plot_logistic_l1_l2_sparsity.html -
Multiclass Receiver Operating Characteristic (R...
This example describes the use of the Receiver Operating Characteristic (ROC) metric to evaluate the quality of multiclass classifiers. ROC curves typically feature true positive rate (TPR) on the ...scikit-learn.org/stable/auto_examples/model_selection/plot_roc.html -
Dimensionality Reduction with Neighborhood Comp...
Sample usage of Neighborhood Components Analysis for dimensionality reduction. This example compares different (linear) dimensionality reduction methods applied on the Digits data set. The data set...scikit-learn.org/stable/auto_examples/neighbors/plot_nca_dim_reduction.html -
Target Encoder’s Internal Cross fitting —...
The TargetEncoder replaces each category of a categorical feature with the shrunk mean of the target variable for that category. This method is useful in cases where there is a strong relationship ...scikit-learn.org/stable/auto_examples/preprocessing/plot_target_encoder_cross_val.html -
Regularization path of L1- Logistic Regression ...
Train l1-penalized logistic regression models on a binary classification problem derived from the Iris dataset. The models are ordered from strongest regularized to least regularized. The 4 coeffic...scikit-learn.org/stable/auto_examples/linear_model/plot_logistic_path.html -
Scalable learning with polynomial kernel approx...
This example illustrates the use of PolynomialCountSketch to efficiently generate polynomial kernel feature-space approximations. This is used to train linear classifiers that approximate the accur...scikit-learn.org/stable/auto_examples/kernel_approximation/plot_scalable_poly_kernels.html -
Using KBinsDiscretizer to discretize continuous...
The example compares prediction result of linear regression (linear model) and decision tree (tree based model) with and without discretization of real-valued features. As is shown in the result be...scikit-learn.org/stable/auto_examples/preprocessing/plot_discretization.html -
Semi-supervised Classification on a Text Datase...
This example demonstrates the effectiveness of semi-supervised learning for text classification on TF-IDF features when labeled data is scarce. For such purpose we compare four different approaches...scikit-learn.org/stable/auto_examples/semi_supervised/plot_semi_supervised_newsgroups.html