cv.glm: Compute average AUC with cross-validation
In konstantin-kotochigov/ML-UTILS: Kostyan's functions
Description
Repeats random split, fits GLM model on train dataset and computes AUC on test dataset and calculates average AUC
In further releases will be replaced with more efficient cross-validation techniques
Usage
1
Arguments
formula
formula to fit regression on
data
input data.frame
target.var
target variable name
n
number of repetitions
fit.type
Type of model to use (GLM or RandomForest)
train.rate
fraction of data to set as training (default=0.7)
konstantin-kotochigov/ML-UTILS documentation built on May 17, 2019, 7:30 p.m.
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Description
Repeats random split, fits GLM model on train dataset and computes AUC on test dataset and calculates average AUC In further releases will be replaced with more efficient cross-validation techniques
Usage
1 |
Arguments
formula |
formula to fit regression on |
data |
input data.frame |
target.var |
target variable name |
n |
number of repetitions |
fit.type |
Type of model to use (GLM or RandomForest) |
train.rate |
fraction of data to set as training (default=0.7) |
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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