w.l.svm: Weighted Linear SVM classification Model
In SkadiEye/ITRlearn: Individualized Treatment Rule Learning
Description
Usage
Arguments
Value
See Also
Description
Fit a Weighted Linear SVM classification Model
Usage
1
Arguments
Y
A factor vector with two levels, a binary response.
X
A numeric matrix, the predictors.
W
A numeric matrix, the weights for all samples. The default is 1.
C
The coefficient for the regularizer.
epsilon
A minor value added to make the quadratic system solvable.
Value
Returns a DnnModelObj object.
See Also
SkadiEye/ITRlearn documentation built on May 24, 2019, 1:31 a.m.
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Description Usage Arguments Value See Also
Description
Fit a Weighted Linear SVM classification Model
Usage
1 |
Arguments
Y |
A |
X |
A |
W |
A |
C |
The coefficient for the regularizer. |
epsilon |
A minor value added to make the quadratic system solvable. |
Value
Returns a DnnModelObj object.
See Also
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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