accuracy: Calculate the Accuracy of the Model at Each Probability...

In bmcguir8/mcguiR: Quick Plotting to Compare Regression Models

Description

only supports binary logistic regression at this time

Usage

accuracy(model, data, ind_column, success, failure, na.rm = T)

Arguments

model	regression model to be used
data	training/testing data to use with model, MUST include all predictors in model
ind_column	independent (outcome) variable column in data - please use data$column syntax
success	character vector; how 'success' is coded in data
failure	character vector; how 'failure' is coded in data
na.rm	when T, only returns Probability Thresholds that have both 'correct' and 'incorrect' values

Value

data frame with % correct calls ('correct'), % incorrect calls ('incorrect') and the probability threshold

Examples

## Not run: 
iris2 <- iris[stringr::str_detect(Species, "setosa", negate = T), ]
irismodel <- glm(Species ~ ., data = iris2, family = binomial)
acc_data <- accuracy(irismodel, iris2, iris2$Species, "virginica", "versicolor")
## End(Not run)

bmcguir8/mcguiR documentation built on Jan. 7, 2021, 8:40 p.m.