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Concatenating multiple feature extraction metho...
features__univ_select__k=1, svm__C=0.1 [CV 1/5; 1/18] END features_...nts=1, features__univ_select__k=1, svm__C=0.1;, score=0.933 total...scikit-learn.org/stable/auto_examples/compose/plot_feature_union.html -
SVM with custom kernel — scikit-learn 1.8.0 doc...
0 ], [ 0 , 1.0 ]]) return np . dot ( np . dot ( X...custom kernel: (2 0) k(X, Y) = X ( ) Y.T (0 1) """ M = np . array...scikit-learn.org/stable/auto_examples/svm/plot_custom_kernel.html -
sklearn.model_selection — scikit-learn 1.8.0 do...
Tools for model selection, such as cross validation and hyper-parameter tuning. User guide. See the Cross-validation: evaluating estimator performance, Tuning the hyper-parameters of an estimator, ...scikit-learn.org/stable/api/sklearn.model_selection.html -
Map data to a normal distribution — scikit-lear...
axes_idxs = [ ( 0 , 3 , 6 , 9 ), ( 1 , 4 , 7 , 10 ), ( 2 , 5 , 8...= rng . uniform ( low = 0 , high = 1 , size = size ) # bimodal...scikit-learn.org/stable/auto_examples/preprocessing/plot_map_data_to_normal.html -
1.7. Gaussian Processes — scikit-learn 1.8.0 do...
constant_value = 1.0 , constant_value_bounds = ( 0.0 , 10.0 )) * RBF...k1__k1__constant_value : 1.0 k1__k1__constant_value_bounds : (0.0, 10.0) k1__k2...scikit-learn.org/stable/modules/gaussian_process.html -
2.7. Novelty and Outlier Detection — scikit-lea...
([[ - 1 , - 1 ], [ - 2 , - 1 ], [ - 3 , - 2 ], [ 0 , 0 ], [ -...Inliers are labeled 1, while outliers are labeled -1. The predict method...scikit-learn.org/stable/modules/outlier_detection.html -
3.5. Validation curves: plotting scores to eval...
array([[0.9, 0.9 , 0.9 , 0.96, 0.9 ], [0.9, 0.83, 0.96, 0.96, 0.93],...array([[1. , 0.93, 1. , 1. , 0.96], [1. , 0.96, 1. , 1. , 0.96],...scikit-learn.org/stable/modules/learning_curve.html -
Support Vector Machines — scikit-learn 1.8.0 do...
Examples concerning the sklearn.svm module. One-class SVM with non-linear kernel (RBF) Plot classification boundaries with different SVM Kernels Plot different SVM classifiers in the iris dataset P...scikit-learn.org/stable/auto_examples/svm/index.html -
sklearn.feature_selection — scikit-learn 1.8.0 ...
Feature selection algorithms. These include univariate filter selection methods and the recursive feature elimination algorithm. User guide. See the Feature selection section for further details.scikit-learn.org/stable/api/sklearn.feature_selection.html -
sklearn.neural_network — scikit-learn 1.8.0 doc...
Models based on neural networks. User guide. See the Neural network models (supervised) and Neural network models (unsupervised) sections for further details.scikit-learn.org/stable/api/sklearn.neural_network.html