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2.2. Manifold learning — scikit-learn 1.4.2 doc...
is \(O[D \log(k) N \log(N)] + O[D N k^3] + O[N d^6] + O[d N^2]\)...is \(O[D \log(k) N \log(N)] + O[D N k^3] + O[k^2 d] + O[d N^2]\)...scikit-learn.org/stable/modules/manifold.html -
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 -
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 -
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 -
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.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 -
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 -
sklearn.preprocessing.OrdinalEncoder — scikit-l...
“a” and “d” are considered infrequent and..."b" ] * 20 + [ "c" ] * 10 + [ "d" ] * 3 + [ np . nan ]], ... dtype...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OrdinalEncoder.html