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ARDRegression — scikit-learn 1.5.0 documentation
is defined as \((1 - \frac{u}{v})\) , where \(u\) is the residual...((y_true - y_pred)** 2).sum() and \(v\) is the total sum of squares...scikit-learn.org/stable/modules/generated/sklearn.linear_model.ARDRegression.html -
DummyRegressor — scikit-learn 1.5.0 documentation
coefficient R^2 is defined as (1 - u/v) , where u is the residual sum...((y_true - y_pred) ** 2).sum() and v is the total sum of squares ((y_true...scikit-learn.org/stable/modules/generated/sklearn.dummy.DummyRegressor.html -
Lasso — scikit-learn 1.5.0 documentation
is defined as \((1 - \frac{u}{v})\) , where \(u\) is the residual...((y_true - y_pred)** 2).sum() and \(v\) is the total sum of squares...scikit-learn.org/stable/modules/generated/sklearn.linear_model.Lasso.html -
ElasticNetCV — scikit-learn 1.5.0 documentation
is defined as \((1 - \frac{u}{v})\) , where \(u\) is the residual...((y_true - y_pred)** 2).sum() and \(v\) is the total sum of squares...scikit-learn.org/stable/modules/generated/sklearn.linear_model.ElasticNetCV.html -
KernelRidge — scikit-learn 1.5.0 documentation
is defined as \((1 - \frac{u}{v})\) , where \(u\) is the residual...((y_true - y_pred)** 2).sum() and \(v\) is the total sum of squares...scikit-learn.org/stable/modules/generated/sklearn.kernel_ridge.KernelRidge.html -
plot_kmeans_digits.ipynb
score\ncompl completeness score\nv-meas V measure\nARI adjusted Rand index\nAMI...metrics.completeness_score,\n metrics.v_measure_score,\n metrics.adjusted_rand_score,\n...scikit-learn.org/stable/_downloads/6bf322ce1724c13e6e0f8f719ebd253c/plot_kmeans_digits.ipynb -
about.rst.txt
V. and Thirion, B. and Grisel, O....P. and Weiss, R. and Dubourg, V. and Vanderplas, J. and Passos,...scikit-learn.org/stable/_sources/about.rst.txt -
ElasticNet — scikit-learn 1.5.0 documentation
is defined as \((1 - \frac{u}{v})\) , where \(u\) is the residual...((y_true - y_pred)** 2).sum() and \(v\) is the total sum of squares...scikit-learn.org/stable/modules/generated/sklearn.linear_model.ElasticNet.html -
LassoCV — scikit-learn 1.5.0 documentation
is defined as \((1 - \frac{u}{v})\) , where \(u\) is the residual...((y_true - y_pred)** 2).sum() and \(v\) is the total sum of squares...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LassoCV.html -
After 40 Years In The Making, Francis Ford Copp...
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