Binary Logistic Regression: Classification Table

Description

Binary Logistic Regression: Classification Table

Usage

classification_table(model, response)

Arguments

Details

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

Examples

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])

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(AutoModel)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/AutoModel/classification_table.Rd_%03d_medium.png", width=480, height=480)
> ### Name: classification_table
> ### Title: Binary Logistic Regression: Classification Table
> ### Aliases: classification_table
> 
> ### ** Examples
> 
> formulas <- create_formula_objects("am", c("hp", "mpg"), c("disp"),
+ c("drat"))
> mtcars_models <- create_model_objects(formulas, data=mtcars,
+ type="binomial")
Warning message:
glm.fit: fitted probabilities numerically 0 or 1 occurred 
> last_model <- mtcars_models[[length(mtcars_models)]]
> classification_table(last_model, last_model$model[,1])
       Actual
Predict  0  1
      0 18  0
      1  1 13
Specificity:  0.9285714 
Sensitivity:  1 
Total Accuracy:  0.96875 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>