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Results 21 - 30 of 185 for d (0.07 sec)
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sklearn.linear_model.PoissonRegressor — 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.PoissonRegressor.html -
sklearn.utils.Bunch — scikit-learn 1.4.2 docume...
all items from D. copy ( ) → a shallow copy of D fromkeys ( iterable...method, then does: for k in E: D[k] = E[k] If E is present and...scikit-learn.org/stable/modules/generated/sklearn.utils.Bunch.html -
neighbors.rst.txt
:math:`D` dimensions, this approach scales as :math:`O[D N^2]`....refers to the dimension :math:`d \le D` of a manifold on which the...scikit-learn.org/stable/_sources/modules/neighbors.rst.txt -
1.8. Cross decomposition — scikit-learn 1.4.2 d...
\(X \in \mathbb{R}^{n \times d}\) and \(Y \in \mathbb{R}^{n \times...compute \(u_k \in \mathbb{R}^d\) and \(v_k \in \mathbb{R}^t\)...scikit-learn.org/stable/modules/cross_decomposition.html -
Putting it all together — scikit-learn 1.4.2 do...
"n_samples: %d " % n_samples ) print ( "n_features: %d " % n_features..."Extracting the top %d eigenfaces from %d faces" % ( n_components...scikit-learn.org/stable/tutorial/statistical_inference/putting_together.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 -
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 -
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.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 -
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