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Image denoising using dictionary learning ̵...
2 , 2 ) difference = image - reference...copy () distorted [:, width // 2 :] += 0.075 * np . random . randn...scikit-learn.org/stable/auto_examples/decomposition/plot_image_denoising.html -
RepeatedKFold — scikit-learn 1.8.0 docume...
2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 , 4 ]]) >>>...RepeatedKFold ( n_splits = 2 , n_repeats = 2 , random_state = 2652124...scikit-learn.org/stable/modules/generated/sklearn.model_selection.RepeatedKFold.html -
mean_variance_axis — scikit-learn 1.8.0 d...
2 , 2 ]) >>> data = np . array ([ 8 , 1 , 2 , 5...>>> scale = np . array ([ 2 , 3 , 2 ]) >>> csr = sparse...scikit-learn.org/stable/modules/generated/sklearn.utils.sparsefuncs.mean_variance_axis.html -
Single estimator versus bagging: bias-variance ...
- ( x ** 2 )) + 1.5 * np . exp ( - (( x - 2 ) ** 2 )) def generate...{0} : {1:.4f} (error) = {2:.4f} (bias^2) " " + {3:.4f}...scikit-learn.org/stable/auto_examples/ensemble/plot_bias_variance.html -
1.5. Stochastic Gradient Descent — scikit...
:= \frac{1}{2} \sum_{j=1}^{m} w_j^2 = ||w||_2^2\) , \(L_1\) norm:...>>> clf . predict ([[ 2. , 2. ]]) array([1]) SGD fits a...scikit-learn.org/stable/modules/sgd.html -
3.1. Cross-validation: evaluating estimator per...
2 , 2 , 2 , 2 ] >>> groups = [ 1 , 1 , 2 , 2 , 3...)) [2 3] [0 1] [1 3] [0 2] [1 2] [0 3] [0 3] [1 2] [0 2] [1 3]...scikit-learn.org/stable/modules/cross_validation.html -
sphinx-design.min.css
sd-g-2,.sd-gy-2{--sd-gutter-y: 0.5rem}.sd-g-2,.sd-gx-2{--sd-gutter-x:...!important}.sd-p-2{padding:.5rem !important}.sd-pt-2,.sd-py-2{padding-top:.5rem...scikit-learn.org/stable/_static/sphinx-design.min.css -
Comparison of kernel ridge and Gaussian process...
period of this sine is thus \(2 \pi\) . We will reuse this information..."True signal" , linewidth = 2 ) plt . scatter ( training_data...scikit-learn.org/stable/auto_examples/gaussian_process/plot_compare_gpr_krr.html -
r2_score — scikit-learn 1.8.0 documentation
= [ - 2 , - 2 , - 2 ] >>> y_pred = [ - 2 , - 2 , - 2...= [ - 2 , - 2 , - 2 ] >>> y_pred = [ - 2 , - 2 , - 2...scikit-learn.org/stable/modules/generated/sklearn.metrics.r2_score.html -
PoissonRegressor — scikit-learn 1.8.0 doc...
determination R^2. R^2 uses squared error and D^2 uses the deviance...() >>> X = [[ 1 , 2 ], [ 2 , 3 ], [ 3 , 4 ], [ 4 , 3...scikit-learn.org/stable/modules/generated/sklearn.linear_model.PoissonRegressor.html