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インストール手順
fess.codelibs.org/ja/setup.html -
Installing the development version of scikit-le...
Editable mode : pip install -v --no-use-pep517 --no-build-isolation...have to run the pip install -v --no-use-pep517 --no-build-isolation...scikit-learn.org/stable/developers/advanced_installation.html -
2.4. Biclustering — scikit-learn 1.5.0 document...
\(u_2 \dots u_{p+1}\) and \(v_2 \dots v_{p+1}\) except in the case...decomposition, \(A_n = U \Sigma V^\top\) , provides the partitions...scikit-learn.org/stable/modules/biclustering.html -
2.9. Neural network models (unsupervised) — sci...
\[\begin{split}h_i \bot h_j | \mathbf{v} \\ v_i \bot v_j | \mathbf{h}\end{split}\]...\[E(\mathbf{v}, \mathbf{h}) = -\sum_i \sum_j w_{ij}v_ih_j - \sum_i...scikit-learn.org/stable/modules/neural_networks_unsupervised.html -
sklearn.random_projection.johnson_lindenstrauss...
eps) ||u - v||^2 < ||p(u) - p(v)||^2 < (1 + eps) ||u - v||^2 Where...Where u and v are any rows taken from a dataset of shape (n_samples,...scikit-learn.org/stable/modules/generated/sklearn.random_projection.johnson_lindenstrauss_min_dim... -
1.8. Cross decomposition — scikit-learn 1.5.0 d...
using the rotation matrix \(V(\Delta^T V)^{-1}\) , accessed via the...to compute \(u_k\) and \(v_k\) , \(v_k\) is never normalized....scikit-learn.org/stable/modules/cross_decomposition.html -
About us — scikit-learn 1.6.dev0 documentation
V . and Thirion , B . and Grisel...and Weiss , R . and Dubourg , V . and Vanderplas , J . and Passos...scikit-learn.org/dev/about.html -
MetaFilter Podcast
at 9:01 AM - 21 comments 185a: V Rising and Severance Random podcast...so here it is. We talk about V Rising, a survive-o-craft vampire...podcast.metafilter.com -
1.2. Linear and Quadratic Discriminant Analysis...
X_k^tX_k = \frac{1}{n - 1} V S^2 V^t\) where \(V\) comes from the SVD...(centered) matrix: \(X_k = U S V^t\) . It turns out that we can...scikit-learn.org/stable/modules/lda_qda.html -
sklearn.svm.NuSVR — scikit-learn 1.4.2 document...
is defined as \((1 - \frac{u}{v})\) , where \(u\) is the residual...((y_true - y_pred)** 2).sum() and \(v\) is the total sum of squares...scikit-learn.org/stable/modules/generated/sklearn.svm.NuSVR.html