|
ProportionalHazardsScore Method |
Overload List| Name | Description | |
|---|---|---|
 | Score(TInput) |
Computes a numerical score measuring the association between
the given input vector and its most strongly
associated class (as predicted by the classifier).
(Inherited from BinaryScoreClassifierBaseTInput.) |
| Score(TInput) |
Computes a numerical score measuring the association between
the given input vector and its most strongly
associated class (as predicted by the classifier).
(Inherited from BinaryScoreClassifierBaseTInput.) |
| Score(Double) |
Computes a numerical score measuring the association between
the given input vector and each class.
|
| Score(Double) |
Computes a numerical score measuring the association between
the given input vector and each class.
|
| Score(TInput, Double) |
Computes a numerical score measuring the association between
the given input vector and each class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.) |
| Score(TInput, Boolean) |
Predicts a class label for the input vector, returning a
numerical score measuring the strength of association of the
input vector to its most strongly related class.
(Inherited from BinaryScoreClassifierBaseTInput.) |
| Score(TInput, Boolean) |
Predicts a class label for each input vector, returning a
numerical score measuring the strength of association of the
input vector to the most strongly related class.
(Inherited from BinaryScoreClassifierBaseTInput.) |
| Score(Double, Double) |
Computes a numerical score measuring the association between
the given input vector and each class.
|
| Score(Double, Double) |
Computes a numerical score measuring the association between
the given input vector and each class.
|
| Score(TInput, Boolean, Double) |
Predicts a class label for each input vector, returning a
numerical score measuring the strength of association of the
input vector to the most strongly related class.
(Inherited from BinaryScoreClassifierBaseTInput.) |
 | Score(TInput, Boolean, Double) | |
| Score(TInput, Boolean, Double) |
See Also