predLossLLRC: Prediction function for the LLRC for a variety of thresholds...
In PNNL-Comp-Mass-Spec/glmnetGLR: glmnetGLR
Description
Let z represent class denoted by the last level of
truthLabels. Then the probability returned by
predict(glmnetFit, newData, type = 'response') is
the probability that the observations belong to class z.
If this probabilty exceeds tau, we will classify the
observation as belonging to z.
Usage
1
2
predLossLLRC(glmnetFit, newData, truthLabels, lossMat, tauVec = seq(0.1, 0.9,
by = 0.1), weight = rep(1, NROW(newData)))
Arguments
glmnetFit
The glmnet fitted object (returned from
PNNL-Comp-Mass-Spec/glmnetGLR documentation built on May 28, 2019, 2:23 p.m.
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Description
Let z represent class denoted by the last level of
truthLabels. Then the probability returned by
predict(glmnetFit, newData, type = 'response') is
the probability that the observations belong to class z.
If this probabilty exceeds tau, we will classify the
observation as belonging to z.
Usage
1 2 | predLossLLRC(glmnetFit, newData, truthLabels, lossMat, tauVec = seq(0.1, 0.9,
by = 0.1), weight = rep(1, NROW(newData)))
|
Arguments
glmnetFit |
The glmnet fitted object (returned from |
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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