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sklearn.gaussian_process.kernels.RationalQuadra...
x_j) = \left( 1 + \frac{d(x_i, x_j)^2 }{ 2\alpha l^2}\right)^{-\alpha}\]...length scale of the kernel and \(d(\cdot,\cdot)\) is the Euclidean...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.RationalQuadratic.html -
sklearn.linear_model.GammaRegressor — scikit-le...
D^2 is defined as \(D^2 = 1-\frac{D(y_{true},y_{pred})}{D_{null}}\)...Compute D^2, the percentage of deviance explained. D^2 is a generalization...scikit-learn.org/stable/modules/generated/sklearn.linear_model.GammaRegressor.html -
sklearn.manifold.Isomap — scikit-learn 1.4.2 do...
frobenius_norm[K(D) - K(D_fit)] / n_samples Where D is the matrix...isomap kernel: K(D) = -0.5 * (I - 1/n_samples) * D^2 * (I - 1/n_samples)...scikit-learn.org/stable/modules/generated/sklearn.manifold.Isomap.html -
sklearn.linear_model.TweedieRegressor — scikit-...
D^2 is defined as \(D^2 = 1-\frac{D(y_{true},y_{pred})}{D_{null}}\)...Compute D^2, the percentage of deviance explained. D^2 is a generalization...scikit-learn.org/stable/modules/generated/sklearn.linear_model.TweedieRegressor.html -
sklearn.metrics.pairwise_distances — scikit-lea...
n_samples_Y) A distance matrix D such that D_{i, j} is the distance between...for usage examples. Returns : D ndarray of shape (n_samples_X,...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise_distances.html -
4.2. Permutation feature importance — scikit-le...
dataset (training or validation) \(D\) . Compute the reference score...of the model \(m\) on data \(D\) (for instance the accuracy for...scikit-learn.org/stable/modules/permutation_importance.html -
1.7. Gaussian Processes — scikit-learn 1.4.2 do...
coefficients of \(x_d (d = 1, . . . , D)\) and a prior of \(N(0,...\text{exp}\left(- \frac{d(x_i, x_j)^2}{2l^2} \right)\] where \(d(\cdot, \cdot)\)...scikit-learn.org/stable/modules/gaussian_process.html -
sklearn.datasets.make_sparse_coded_signal — sci...
such that D is of shape (n_features, n_components)...default=False By default, Y, D and X are not transposed. New...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_sparse_coded_signal.html -
sklearn.feature_extraction.DictVectorizer — sci...
DictVectorizer ( sparse = False ) >>> D = [{ 'foo' : 1 , 'bar' : 2 },...}] >>> X = v . fit_transform ( D ) >>> X array([[2., 0., 1.], [0.,...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.DictVectorizer.html -
sklearn.gaussian_process.kernels.DotProduct — s...
coefficients of \(x_d (d = 1, . . . , D)\) and a prior of \(N(0,...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.DotProduct.html