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StratifiedGroupKFold — scikit-learn 1.6.1 docum...
print ( f "Fold { i } :" ) ... print ( f " Train: index=...print ( f " Test: index= { test_index } " ) ... print ( f " group=...scikit-learn.org/stable/modules/generated/sklearn.model_selection.StratifiedGroupKFold.html -
plot_hgbt_regression.zip
print(f"Training sample size: {X_train.shape[0]}") print(f"Test...rint(f\"Test sample size: {X_test.shape[0]}\")\nprint(f\"Number...scikit-learn.org/stable/_downloads/ef504a3cb245a55fde178198c8218b4a/plot_hgbt_regression.zip -
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 -
ShuffleSplit — scikit-learn 1.6.1 documentation
print ( f "Fold { i } :" ) ... print ( f " Train: index=...)): ... print ( f "Fold { i } :" ) ... print ( f " Train: index=...scikit-learn.org/stable/modules/generated/sklearn.model_selection.ShuffleSplit.html -
Feature Selection — scikit-learn 1.6.1 document...
scikit-learn.org/stable/auto_examples/feature_selection/index.html -
permutation_test_score — scikit-learn 1.6.1 doc...
) >>> print ( f "Original Score: { score : .3f...Score: 0.810 >>> print ( ... f "Permutation Scores: { permutation_scores...scikit-learn.org/stable/modules/generated/sklearn.model_selection.permutation_test_score.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 -
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 -
KFold — scikit-learn 1.6.1 documentation
print ( f "Fold { i } :" ) ... print ( f " Train: index=...train_index } " ) ... print ( f " Test: index= { test_index }...scikit-learn.org/stable/modules/generated/sklearn.model_selection.KFold.html -
auto_examples_python.zip
randn(1000) f_test, _ = f_regression(X, y) f_test /= np.max(f_test)...with f_0, and negatively correlated with f_1 y = 5 * f_0 + np.sin(10...scikit-learn.org/stable/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip