In previous section, we studied about Goodness of fit for Logistic Regression
library(car)
## Warning: package 'car' was built under R version 3.1.3
vif(Fiberbits_model_1)
## income months_on_network
## 4.590705 4.641040
## Num_complaints number_plan_changes
## 1.018607 1.126892
## relocated monthly_bill
## 1.145847 1.017565
## technical_issues_per_month Speed_test_result
## 1.020648 1.206999
library(caret)
## Warning: package 'caret' was built under R version 3.1.3
## Loading required package: lattice
## Loading required package: ggplot2
## Warning: package 'ggplot2' was built under R version 3.1.3
varImp(Fiberbits_model_1, scale = FALSE)
## Overall
## income 20.81981
## months_on_network 28.65421
## Num_complaints 22.81102
## number_plan_changes 24.93955
## relocated 79.92677
## monthly_bill 13.99490
## technical_issues_per_month 54.58123
## Speed_test_result 93.43471
This will give the absolute value of the Z-score
library(stats)
AIC(Fiberbits_model_1)
## [1] 98377.36
BIC(Fiberbits_model_1)
## [1] 98462.97
The next post is about Model Selection in logistic regression.