- Sort Score
- Result 10 results
- Languages All
- Labels All
Results 131 - 140 of 231 for v (0.05 sec)
-
Elastic integrates Anthropic's Claude 3 models ...
V. in the United States and other...www.elastic.co/blog/ai-security-analytics-integrating-anthropic-claude -
5 stand-out retail use cases for generative AI ...
V. in the United States and other...www.elastic.co/blog/retail-use-cases-generative-ai-elasticsearch -
IDC Market Perspective published on the Elastic...
V. in the United States and other...www.elastic.co/blog/idc-market-perspective-elastic-ai-assistant -
Wikipedia principal eigenvector — scikit-learn ...
V = randomized_svd ( X , 5 , n_iter...names [ i ] for i in np . abs ( V [ 0 ]) . argsort ()[ - 10 :]])...scikit-learn.org/stable/auto_examples/applications/wikipedia_principal_eigenvector.html -
ARDRegression — scikit-learn 1.5.0 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.ARDRegression.html -
DummyRegressor — scikit-learn 1.5.0 documentation
coefficient R^2 is defined as (1 - u/v) , where u is the residual sum...((y_true - y_pred) ** 2).sum() and v is the total sum of squares ((y_true...scikit-learn.org/stable/modules/generated/sklearn.dummy.DummyRegressor.html -
QuadraticDiscriminantAnalysis — scikit-learn 1....
It corresponds to V , the matrix of eigenvectors coming...scikit-learn.org/stable/modules/generated/sklearn.discriminant_analysis.QuadraticDiscriminantAnal... -
KernelRidge — scikit-learn 1.5.0 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.kernel_ridge.KernelRidge.html -
Lasso — scikit-learn 1.5.0 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.Lasso.html -
ElasticNetCV — scikit-learn 1.5.0 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.ElasticNetCV.html