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KFold — scikit-learn 1.6.0 documentation
2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 , 4 ]]) >>>...array ([ 1 , 2 , 3 , 4 ]) >>> kf = KFold ( n_splits = 2 ) >>> kf...scikit-learn.org/stable/modules/generated/sklearn.model_selection.KFold.html -
LassoLarsIC — scikit-learn 1.6.0 documentation
[[ - 2 , 2 ], [ - 1 , 1 ], [ 0 , 0 ], [ 1 , 1 ], [ 2 , 2 ]] >>>...is: ( 1 / ( 2 * n_samples )) * || y - Xw ||^ 2_2 + alpha * ||...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LassoLarsIC.html -
linear_model.rst.txt
x_1 + w_2 x_2 + w_3 x_1 x_2 + w_4 x_1^2 + w_5 x_2^2 The (sometimes...:math:`[x_1, x_2]` to :math:`[1, x_1, x_2, x_1^2, x_1 x_2, x_2^2]`, and...scikit-learn.org/stable/_sources/modules/linear_model.rst.txt -
PolynomialFeatures — scikit-learn 1.6.0 documen...
degree-2 polynomial features are [1, a, b, a^2, ab, b^2]. Read...etc. excluded: x[0] ** 2 , x[0] ** 2 * x[1] , etc. include_bias...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.PolynomialFeatures.html -
auto_examples_python.zip
- l / 2.0) ** 2 + (y - l / 2.0) ** 2 < (l / 2.0) ** 2 mask =...color=colors[y_pred]) plt.xlim(-2.5, 2.5) plt.ylim(-2.5, 2.5) plt.xticks(())...scikit-learn.org/stable/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip -
shuffle — scikit-learn 1.6.0 documentation
2)> >>> X_sparse . toarray () array([[0., 0.], [2., 1.],...y array([2, 1, 0]) >>> shuffle ( y , n_samples = 2 , random_state...scikit-learn.org/stable/modules/generated/sklearn.utils.shuffle.html -
3.4. Metrics and scoring: quantifying the quali...
y_true = [ - 2 , - 2 , - 2 ] >>> y_pred = [ - 2 , - 2 , - 2 ] >>> r2_score...y_true = [ - 2 , - 2 , - 2 ] >>> y_pred = [ - 2 , - 2 , - 2 + 1e-8...scikit-learn.org/dev/modules/model_evaluation.html -
Complaints about 2024? | MetaFilter
posted by tclark at 2:10 PM on December 18 [ 2 favorites ] Boy that...kink! posted by obfuscation at 2:08 PM on December 18 I got a lot...www.metafilter.com/206781/Complaints-about-2024 -
1.6. Nearest Neighbors — scikit-learn 1.6.0 doc...
2 ]]) >>> y = np . array ([ 1 , 1 , 1 , 2 , 2 , 2 ]) >>>...- 1 ], [ - 2 , - 1 ], [ - 3 , - 2 ], [ 1 , 1 ], [ 2 , 1 ], [ 3...scikit-learn.org/stable/modules/neighbors.html -
GammaRegressor — scikit-learn 1.7.dev0 document...
determination R^2. R^2 uses squared error and D^2 uses the deviance...GammaRegressor () >>> X = [[ 1 , 2 ], [ 2 , 3 ], [ 3 , 4 ], [ 4 , 3...scikit-learn.org/dev/modules/generated/sklearn.linear_model.GammaRegressor.html