Please provide help with this question using the A6DATA.csv file below and R programming/R Studio:

A6DATA.csv data :

https://www.dropbox.com/s/gxa0yf2j7mnp1x4/A6DATA.csv?dl=0

Part a:

Assemble logistic regression models with 60%/40%, 70%/30%, and 80%/20% partitioning into training and testing data sets using set.seed(222).

Please help to summarize the training and testing accuracy, sensitivity and specificity for each and compare with 50%/50% performance using the table below. Please recommend and comment on the best model.

Partitioning Accuracy % Sensitivity % Specificity % Training - 50% Testing - 50% ing - 60% Training Testing - 40% Training - 70% Testing - 30% Training - 80% Testing - 20%