wsvm: wsvm to solve the subject-weighted SVM
In sambiostat/RICWL:
Description
Usage
Arguments
Value
Description
wsvm to solve the subject-weighted SVM
Usage
1
Arguments
X:
n by p feature matrix
A:
label
wR:
instance weight
kernel:
propensity score with length n, can be either "rbf" or "linear", default is "linear"
sigma:
hyper-parameter in SVM rbf kernel
C:
hyper-parameter in SVM rbf kernel
e:
least tolerated error
Value
object in rbfcl or linearcf classs
sambiostat/RICWL documentation built on Dec. 31, 2020, 3:17 a.m.
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Description Usage Arguments Value
Description
wsvm to solve the subject-weighted SVM
Usage
1 |
Arguments
X: |
n by p feature matrix |
A: |
label |
wR: |
instance weight |
kernel: |
propensity score with length n, can be either "rbf" or "linear", default is "linear" |
sigma: |
hyper-parameter in SVM rbf kernel |
C: |
hyper-parameter in SVM rbf kernel |
e: |
least tolerated error |
Value
object in rbfcl or linearcf classs
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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