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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 -
ParameterSampler — scikit-learn 1.7.2 documenta...
round ( v , 6 )) for ( k , v ) in d . items ()) ......scikit-learn.org/stable/modules/generated/sklearn.model_selection.ParameterSampler.html -
BernoulliRBM — scikit-learn 1.7.2 documentation
gibbs ( v ) [source] # Perform one Gibbs...Gibbs sampling step. Parameters : v ndarray of shape (n_samples, n_features)...scikit-learn.org/stable/modules/generated/sklearn.neural_network.BernoulliRBM.html -
Bunch — scikit-learn 1.7.2 documentation
v in E: D[k] = v In either case, this is...scikit-learn.org/stable/modules/generated/sklearn.utils.Bunch.html -
TransformedTargetRegressor — scikit-learn 1.7.2...
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.compose.TransformedTargetRegressor.html -
Common problems | APM Server Reference [7.15] |...
s=index&v=true&h=index,stage When stage:..._cat/aliases/apm*transaction*?s=index&v=true&h=alias,index,is_write_index...www.elastic.co/guide/en/apm/server/current/common-problems.html -
elastic-gtr-2024-threat-trends
V. All rights reserved. Threat trends...elastic.co | © 2024 Elasticsearch B.V. All rights reserved. 01 02 04...www.elastic.co/pdf/elastic-gtr-2024-threat-trends -
LarsCV — scikit-learn 1.7.2 documentation
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.linear_model.LarsCV.html -
MultiOutputRegressor — scikit-learn 1.7.2 docum...
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.multioutput.MultiOutputRegressor.html -
LinearRegression — scikit-learn 1.7.2 documenta...
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.linear_model.LinearRegression.html