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plot_hgbt_regression.ipynb
import train_test_split\n\nX_train, X_test, y_train, y_test = train_test_split(X,...train_test_split(X, y, test_size=0.4, shuffle=False)\n\nprint(f\"Training...scikit-learn.org/stable/_downloads/cb9a8a373677fb481fe43a11d8fa0e94/plot_hgbt_regression.ipynb -
SGDClassifier — scikit-learn 1.5.0 documentation
classification of text documents Out-of-core classification of text documents...on a Text Dataset Semi-supervised Classification on a Text Dataset...scikit-learn.org/stable/modules/generated/sklearn.linear_model.SGDClassifier.html -
Contributing — scikit-learn 1.6.dev0 documentation
sklearn/linear_model/tests/test_logistic.py to run the tests specific to...sklearn path/to/tests See also Testing and improving test coverage ....scikit-learn.org/dev/developers/contributing.html -
LogisticRegression — scikit-learn 1.5.0 documen...
the mean accuracy on the given test data and labels. In multi-label...shape (n_samples, n_features) Test samples. y array-like of shape...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html -
pydata-sphinx-theme.js
test(e)&&o.test(e),n=(e,t,n)=>{u(n);const.../i.test(e.key)?document.activeElement===t&&/Escape/i.test(e....scikit-learn.org/dev/_static/scripts/pydata-sphinx-theme.js -
OrthogonalMatchingPursuit — scikit-learn 1.5.0 ...
n_features) Test samples. For some estimators...y_true.mean()) ** 2).sum() . The best possible score is 1.0 and it...scikit-learn.org/stable/modules/generated/sklearn.linear_model.OrthogonalMatchingPursuit.html -
faq.rst.txt
:ref:`text_feature_extraction` for the built-in *text vectorizers*....^^^^^^^^^^ scikit-learn is regularly tested and maintained to work with...scikit-learn.org/stable/_sources/faq.rst.txt -
auto_examples_jupyter.zip
X_test, y_train, y_test = train_test_split(\n X, y, test_size=0.25,...\"%(n_test)6d test docs (%(n_test_pos)6d positive) \" % test_stats\n...scikit-learn.org/stable/_downloads/6f1e7a639e0699d6164445b55e6c116d/auto_examples_jupyter.zip -
DecisionTreeClassifier — scikit-learn 1.5.0 doc...
splitter {“best”, “random”}, default=”best” The strategy used...Supported strategies are “best” to choose the best split and “random”...scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeClassifier.html -
model_evaluation.rst.txt
ratio (pre-test and post-tests): .. math:: \text{post-test odds} =...\frac{\text{pre-test probability}}{1 - \text{pre-test probability}},...scikit-learn.org/stable/_sources/modules/model_evaluation.rst.txt