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plot_release_highlights_1_8_0.py
or with conda:: conda install -c conda-forge scikit-learn """ #...ncols=3, sharey=True, ) for i, c in enumerate(ts.classes_): Ca...scikit-learn.org/stable/_downloads/2f7d0c4f8bbd7c7e4062e34c1bffe66a/plot_release_highlights_1_8_0.py -
plot_release_highlights_1_8_0.zip
or with conda:: conda install -c conda-forge scikit-learn """ #...ncols=3, sharey=True, ) for i, c in enumerate(ts.classes_): Ca...scikit-learn.org/stable/_downloads/195570df7730e31327589be9e4984333/plot_release_highlights_1_8_0... -
plot_classifier_comparison.zip
C=0.025, random_state=42), SVC(gamma=2, C=1, random_state=42),...SVC(kernel=\"linear\", C=0.025, random_state=42),\n SVC(gamma=2, C=1, random_state=42),\n...scikit-learn.org/stable/_downloads/ce35bcc69acbd491cf7ac77fa17889d5/plot_classifier_comparison.zip -
bootstrap.js
F="y"===C?n:r,H="y"===C?s:o,W="y"===C?"height":"width",z=x[C],R=...;x[C]=ht,M[C]=ht-z}if(u){var dt,ut="x"===C?n:r,ft="x"===C?s:...scikit-learn.org/stable/_static/scripts/bootstrap.js -
plot_classifier_comparison.py
C=0.025, random_state=42), SVC(gamma=2, C=1, random_state=42),...ax.scatter(X_train[:, 0], X_train[:, 1], c=y_train, cmap=cm_bright, edgecolors="k")...scikit-learn.org/stable/_downloads/2da0534ab0e0c8241033bcc2d912e419/plot_classifier_comparison.py -
plot_classifier_comparison.ipynb
C=0.025, random_state=42),\n SVC(gamma=2, C=1, random_state=42),\n...ax.scatter(X_train[:, 0], X_train[:, 1], c=y_train, cmap=cm_bright, edgecolors=\"k\")\n...scikit-learn.org/stable/_downloads/3438aba177365cb595921cf18806dfa7/plot_classifier_comparison.ipynb -
plot_release_highlights_1_8_0.ipynb
with conda::\n\n conda install -c conda-forge scikit-learn\n" ]...ncols=3,\n sharey=True,\n)\nfor i, c in enumerate(ts.classes_):\n ...scikit-learn.org/stable/_downloads/826f1a05a1b6ad38fb98368f39e30aa6/plot_release_highlights_1_8_0... -
pydata-sphinx-theme.js
i=c(n,o);return 0!==i?i:a&&s?c(a.split("."),s.... i=o&&e.preferred,c=!o&&!r&&e.match;(i||c)&&(a.classList.add...scikit-learn.org/stable/_static/scripts/pydata-sphinx-theme.js -
plot_release_highlights_1_7_0.py
or with conda:: conda install -c conda-forge scikit-learn """ #...d=False), LogisticRegression(C=2.0)) model # %% # Custom validation...scikit-learn.org/stable/_downloads/27dd4dbb41dee53fc86e0d5b6d3254d3/plot_release_highlights_1_7_0.py -
auto_examples_python.zip
"P(C)", "P(w0|C)", "P(w1|C)", sep="\t") for k,...".join( f"{(c / n_rows * 100):.0f}% {name}" for name, c in counter.most_common(3)...scikit-learn.org/stable/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip