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bootstrap.js
nce[f]-d[f]-i.rects.popper[p],y=d[f]-i.rects.reference[f],w=...,k,M)),F=y===f?j:I,B={top:$.top-F.top+C.top,bottom:F.bottom-...scikit-learn.org/stable/_static/scripts/bootstrap.js -
Feature Selection — scikit-learn 1.5.0 document...
Comparison of F-test and mutual information Comparison of F-test and...scikit-learn.org/stable/auto_examples/feature_selection/index.html -
1.16. Probability calibration — scikit-learn 1....
(y_i - \hat{f}_i)^2\] subject to \(\hat{f}_i \geq \hat{f}_j\) whenever...: \[p(y_i = 1 | f_i) = \frac{1}{1 + \exp(A f_i + B)} \,,\] where...scikit-learn.org/stable/modules/calibration.html -
1.17. Neural network models (supervised) — scik...
algorithm that learns a function \(f: R^m \rightarrow R^o\) by training...neuron MLP learns the function \(f(x) = W_2 g(W_1^T x + b_1) + b_2\)...scikit-learn.org/stable/modules/neural_networks_supervised.html -
ensemble.rst.txt
F(x_i))}{\partial F(x_i)} \right]_{F=F_{m - 1}}. .....\frac{\partial l(y_i, F(x_i))}{\partial F(x_i)} \right]_{F=F_{m - 1}}` is...scikit-learn.org/stable/_sources/modules/ensemble.rst.txt -
sklearn.utils.validation.check_is_fitted — scik...
print ( f "Model is not fitted yet." ) Model...scikit-learn.org/stable/modules/generated/sklearn.utils.validation.check_is_fitted.html -
feature_selection.rst.txt
we can use a F-test to retrieve the two best...sklearn.feature_selection import f_classif >>> X, y = load_iris(return_X_y=True)...scikit-learn.org/stable/_sources/modules/feature_selection.rst.txt -
1.7. Gaussian Processes — scikit-learn 1.5.0 do...
prior on a latent function \(f\) , which is then squashed through...classification. The latent function \(f\) is a so-called nuisance function,...scikit-learn.org/stable/modules/gaussian_process.html -
plot_release_highlights_1_4_0.ipynb
decision_function(X_test)\nprint(f\"ROC AUC score is {roc_auc_score(y_test,..."outputs": [], "source": [ "print(f\"Output type: {type(df_out)}\")"...scikit-learn.org/stable/_downloads/53490cdb42c3c07ba8cccd1c4ed4dca4/plot_release_highlights_1_4_0... -
sklearn.gaussian_process.kernels.Hyperparameter...
in sorted ( params ): print ( f " { key } : { params [ key ] }...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.Hyperparameter.html