- Sort Score
- Result 10 results
- Languages All
- Labels All
Results 51 - 60 of 266 for v (0.07 sec)
-
KernelRidge — scikit-learn 1.7.1 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 -
ARDRegression — scikit-learn 1.7.1 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 -
Data tiers | Elastic Docs
v=true to check that the restored..._cat/indices/<backing-index-name>?v=true to check. Once your data...www.elastic.co/docs/manage-data/lifecycle/data-tiers -
RidgeCV — scikit-learn 1.7.1 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.RidgeCV.html -
NuSVR — scikit-learn 1.7.1 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.svm.NuSVR.html -
Lasso — scikit-learn 1.7.1 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 1.7.1 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 -
LassoLarsCV — scikit-learn 1.7.1 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.LassoLarsCV.html -
decomposition.rst.txt
V^*) = \underset{U, V}{\operatorname{arg\,min\,}}...multiply it with :math:`V_k`: .. math:: X' = X V_k .. note:: Most treatments...scikit-learn.org/stable/_sources/modules/decomposition.rst.txt -
BaggingRegressor — scikit-learn 1.7.1 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.ensemble.BaggingRegressor.html