classification_summary {bayesrules} | R Documentation |
Posterior Classification Summaries
Description
Given a set of observed data including a binary response variable y and an rstanreg model of y, this function returns summaries of the model's posterior classification quality. These summaries include a confusion matrix as well as estimates of the model's sensitivity, specificity, and overall accuracy.
Usage
classification_summary(model, data, cutoff = 0.5)
Arguments
model |
an rstanreg model object with binary y |
data |
data frame including the variables in the model, both response y and predictors x |
cutoff |
probability cutoff to classify a new case as positive (0.5 is the default) |
Value
a list
Examples
x <- rnorm(20)
z <- 3*x
prob <- 1/(1+exp(-z))
y <- rbinom(20, 1, prob)
example_data <- data.frame(x = x, y = y)
example_model <- rstanarm::stan_glm(y ~ x, data = example_data, family = binomial)
classification_summary(model = example_model, data = example_data, cutoff = 0.5)
[Package bayesrules version 0.0.2 Index]