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2.4. Biclustering — scikit-learn 1.7.2 document...
2 ]) >>> data [ rows , columns ] array([[ 1, 2], [21,...as follows: \[A_n = R^{-1/2} A C^{-1/2}\] Where \(R\) is the diagonal...scikit-learn.org/stable/modules/biclustering.html -
DotProduct — scikit-learn 1.7.2 documentation
\sigma_0^2)\) on the bias. The DotProduct...of the kernel. For \(\sigma_0^2 =0\) , the kernel is called the...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.DotProduct.html -
LocalOutlierFactor — scikit-learn 1.7.2 documen...
array([[2]])) As you can see, it returns [[0.5]], and [[2]], which..., metric = 'minkowski' , p = 2 , metric_params = None , contamination...scikit-learn.org/stable/modules/generated/sklearn.neighbors.LocalOutlierFactor.html -
ExpSineSquared — scikit-learn 1.7.2 documentation
\text{exp}\left(- \frac{ 2\sin^2(\pi d(x_i, x_j)/p) }{ l^ 2} \right)\] where...0.0144 >>> gpr . predict ( X [: 2 ,:], return_std = True ) (array([425.6,...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.ExpSineSquared.html -
OrdinalEncoder — scikit-learn 1.7.2 documentation
transform ( X_test ) array([[2.], [0.], [1.], [2.], [3.], [4.]]) fit (...scikit-learn 1.2 Release Highlights for scikit-learn 1.2 Release Highlights...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OrdinalEncoder.html -
7.2. Feature extraction — scikit-learn 1.7.2 do...
2.0986]}{\sqrt{\big(3^2 + 0^2 + 2.0986^2\big)}} = [...\frac{v}{||v||_2} = \frac{v}{\sqrt{v{_1}^2 + v{_2}^2 + \dots + v{_n}^2}}\)...scikit-learn.org/stable/modules/feature_extraction.html -
gen_even_slices — scikit-learn 1.7.2 documentation
2, None), slice(2, 4, None), ..., slice(8,...[slice(0, 1, None), slice(1, 2, None), ..., slice(9, 10, None)]...scikit-learn.org/stable/modules/generated/sklearn.utils.gen_even_slices.html -
roc_auc_score — scikit-learn 1.7.2 documentation
the standardized partial AUC [2] over the range [0, max_fpr] is...under of the ROC as follows: G = 2 * AUC - 1 Where G is the Gini...scikit-learn.org/stable/modules/generated/sklearn.metrics.roc_auc_score.html -
FeatureHasher — scikit-learn 1.7.2 documentation
'cat' : 2 , 'elephant' : 4 },{ 'dog' : 2 , 'run' : 5 }]...0., 0., 0., 0., 0., 2.], [ 0., 0., 0., -2., -5., 0., 0., 0., 0.,...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.FeatureHasher.html -
Kernel — scikit-learn 1.7.2 documentation
length_scale = 2.0 ) >>> X = np . array ([[ 1 , 2 ], [ 3 , 4 ]])..., X if Y is None else Y ) ** 2 ... def diag ( self , X ): ......scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.Kernel.html