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pydata-sphinx-theme.js
align-baseline";const f=document.createElement("i");p.append(f),f.classList="fa-solid...theme.`),m.onchange="auto"==e?h:""}function f(){const e=document.documentEl...scikit-learn.org/dev/_static/scripts/pydata-sphinx-theme.js -
4.1. Partial Dependence and Individual Conditio...
\mathbb{E}_{X_C}\left[ f(x_S, X_C) \right]\\ &= \int f(x_S, x_C) p(x_C)...dependence of the response \(f\) at a point \(x_S\) is defined...scikit-learn.org/stable/modules/partial_dependence.html -
plot_hgbt_regression.ipynb
rint(f\"Test sample size: {X_test.shape[0]}\")\nprint(f\"Number...test_size=0.4, shuffle=False)\n\nprint(f\"Training sample size: {X_tra...scikit-learn.org/stable/_downloads/cb9a8a373677fb481fe43a11d8fa0e94/plot_hgbt_regression.ipynb -
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 -
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/dev/_static/scripts/bootstrap.js -
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 -
decomposition.rst.txt
F. Bach, J. Ponce, G. Sapiro, 2009..._ R. Jenatton, G. Obozinski, F. Bach, 2009 .. _kernel_PCA: Kernel...scikit-learn.org/stable/_sources/modules/decomposition.rst.txt -
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 -
preprocessing.rst.txt
formula :math:`G^{-1}(F(X))` where :math:`F` is the cumulative distribution...distribution function :math:`F` then :math:`F(X)` is uniformly distributed...scikit-learn.org/stable/_sources/modules/preprocessing.rst.txt -
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