pred_assess: pred_assess
In LewisLabUCSD/RegressionModelPipeline: Pipeline for feature selection, interaction assessment, regression modeling and prediction assessment for 1-1000s of features
Description
Usage
Arguments
Value
View source: R/performance_assessment.r
Description
MAIN cross validation assessment. There are 2 main usage modes. 1) provide predictions by setting pred and truth, 2) provide mod and dat to generate predictions to evaluate.
Usage
1
2
Arguments
resp,
a character vector of the names of dependent/response variables in df
pred,
option 1 parameter: matrix of predictions (observations x fold)
truth,
option 1 parameter: matrix of ground truth values (observations x fold)
mod,
option 2 parameter: a trained model: glm(resp~...) or lm(resp~...)
dat,
option 2 parameter: a data.frame containing all variables used in the mod model.
Value
list of performance assessments
LewisLabUCSD/RegressionModelPipeline documentation built on Jan. 11, 2021, 10:33 p.m.
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Description Usage Arguments Value
View source: R/performance_assessment.r
Description
MAIN cross validation assessment. There are 2 main usage modes. 1) provide predictions by setting pred and truth, 2) provide mod and dat to generate predictions to evaluate.
Usage
1 2 |
Arguments
resp, |
a character vector of the names of dependent/response variables in df |
pred, |
option 1 parameter: matrix of predictions (observations x fold) |
truth, |
option 1 parameter: matrix of ground truth values (observations x fold) |
mod, |
option 2 parameter: a trained model: glm(resp~...) or lm(resp~...) |
dat, |
option 2 parameter: a data.frame containing all variables used in the mod model. |
Value
list of performance assessments
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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