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plot_multi_metric_evaluation.zip
sample_score_mean = results["mean_%s_%s" % (sample, scorer)] sample_score_std...sample_score_std = results["std_%s_%s" % (sample, scorer)] ax.fill_between(...scikit-learn.org/stable/_downloads/535778bfbc9b4881da3e662bc2ea8484/plot_multi_metric_evaluation.zip -
plot_multi_metric_evaluation.py
sample_score_mean = results["mean_%s_%s" % (sample, scorer)] sample_score_std...sample_score_std = results["std_%s_%s" % (sample, scorer)] ax.fill_between(...scikit-learn.org/stable/_downloads/dedbcc9464f3269f4f012f4bfc7d16da/plot_multi_metric_evaluation.py -
plot_multi_metric_evaluation.rst.txt
sample_score_mean = results["mean_%s_%s" % (sample, scorer)] sample_score_std...sample_score_std = results["std_%s_%s" % (sample, scorer)] ax.fill_between(...scikit-learn.org/stable/_sources/auto_examples/model_selection/plot_multi_metric_evaluation.rst.txt -
plot_discretization_strategies.zip
set_title("strategy='%s'" % (strategy,), size=14) i +=...0:\n ax.set_title(\"strategy='%s'\" % (strategy,), size=14)\n\n...scikit-learn.org/stable/_downloads/7b16734166ab4280e940d7fb89dd6113/plot_discretization_strategie... -
plot_pca_iris.zip
dataset # ---------- # # Let's first plot the pairs of features...sepal width and length, there's still # overlap between the Versicolor...scikit-learn.org/stable/_downloads/99402c7ce7a6ab7fafcb48caa3c9447b/plot_pca_iris.zip -
plot_discretization_strategies.py
set_title("strategy='%s'" % (strategy,), size=14) i +=...scikit-learn.org/stable/_downloads/43e84df0b93ff974da370e8da900f2ee/plot_discretization_strategie... -
plot_discretization_strategies.rst.txt
set_title("strategy='%s'" % (strategy,), size=14) i +=...scikit-learn.org/stable/_sources/auto_examples/preprocessing/plot_discretization_strategies.rst.txt -
plot_pca_iris.rst.txt
the Iris dataset ---------- Let's first plot the pairs of features...sepal width and length, there's still overlap between the Versicolor...scikit-learn.org/stable/_sources/auto_examples/decomposition/plot_pca_iris.rst.txt -
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