classification_table: Binary Logistic Regression: Classification Table

Description Usage Arguments Details Examples

Description

Binary Logistic Regression: Classification Table

Usage

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classification_table(model, response)

Arguments

model

A binary logistic regression model object.

response

The dependent variable in model.

Details

Creates classification table for binary logistic regresison model using optimal cut point for accuracy.

Examples

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formulas <- create_formula_objects("am", c("hp", "mpg"), c("disp"),
c("drat"))
mtcars_models <- create_model_objects(formulas, data=mtcars,
type="binomial")
last_model <- mtcars_models[[length(mtcars_models)]]
classification_table(last_model, last_model$model[,1])

Example output

Warning message:
glm.fit: fitted probabilities numerically 0 or 1 occurred 
       Actual
Predict  0  1
      0 18  0
      1  1 13
Specificity:  0.9285714 
Sensitivity:  1 
Total Accuracy:  0.96875 

AutoModel documentation built on May 1, 2019, 9:14 p.m.