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PLSSVD — scikit-learn 1.8.0 documentation
[ 2. , 2. , 2. ], ... [ 2. , 5. , 4. ]]) >>>...([[ 0.1 , - 0.2 ], ... [ 0.9 , 1.1 ], ... [ 6.2 , 5.9 ], ... [...scikit-learn.org/stable/modules/generated/sklearn.cross_decomposition.PLSSVD.html -
Two-class AdaBoost — scikit-learn 1.8.0 documen...
cov = 2.0 , n_samples = 200 , n_features = 2 , n_classes = 2 , random_state...= 300 , n_features = 2 , n_classes = 2 , random_state = 1 ) X...scikit-learn.org/stable/auto_examples/ensemble/plot_adaboost_twoclass.html -
confusion_matrix — scikit-learn 1.8.0 documenta...
= [ 2 , 0 , 2 , 2 , 0 , 1 ] >>> y_pred = [ 0 , 0 , 2 , 2 , 0...0 , 2 ] >>> confusion_matrix ( y_true , y_pred ) array([[2, 0,...scikit-learn.org/stable/modules/generated/sklearn.metrics.confusion_matrix.html -
Thread pool settings | Reference
of allocated processors * 3) / 2) + 1 , and queue_size of 1000...# of allocated processors ) / 2 , and queue_size of 1000 . get...www.elastic.co/docs/reference/elasticsearch/configuration-reference/thread-pool-settings -
RegressorChain — scikit-learn 1.8.0 documentation
2 ], [ 1 , 1 ], [ 2 , 0 ]] >>> chain = RegressorChain...predict ( X ) array([[0., 2.], [1., 1.], [2., 0.]]) fit ( X , Y ,...scikit-learn.org/stable/modules/generated/sklearn.multioutput.RegressorChain.html -
RationalQuadratic — scikit-learn 1.8.0 document...
x_j)^2 }{ 2\alpha l^2}\right)^{-\alpha}\] where...>>> gpc . predict_proba ( X [: 2 ,:]) array([[0.8881, 0.0566, 0.05518],...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.RationalQuadratic.html -
1.1. Linear Models — scikit-learn 1.8.0 documen...
\frac{n}{2} \log(2 \pi) - \frac{n}{2} \log(\sigma^2) - \frac{\sum_{i=1}^{n}...(y_i - \hat{y}_i)^2}{2\sigma^2}\] where \(\sigma^2\) is an estimate...scikit-learn.org/stable/modules/linear_model.html -
RegressorMixin — scikit-learn 1.8.0 documentation
2 ], [ 2 , 3 ], [ 3 , 4 ]]) >>> y =...float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...scikit-learn.org/stable/modules/generated/sklearn.base.RegressorMixin.html -
feature_extraction.rst.txt
2.0986]}{\sqrt{\big(3^2 + 0^2 + 2.0986^2\big)}} = [...(one_image, (2, 2)) >>> patches.shape (9, 2, 2, 3) >>> patches[4,...scikit-learn.org/stable/_sources/modules/feature_extraction.rst.txt -
inplace_swap_row — scikit-learn 1.8.0 doc...
2 , 2 ]) >>> data = np . array ([ 8 , 2 , 5 ])...>>> indptr = np . array ([ 0 , 2 , 3 , 3 , 3 ]) >>> indices...scikit-learn.org/stable/modules/generated/sklearn.utils.sparsefuncs.inplace_swap_row.html