Patients with liver disease have been continuously increasing because of excessive consumption of alcohol, inhale of harmful gases, intake of contaminated food, pickles and drugs. In an effort to reduce the burden on doctors, the government has hired you as a data scientist to build a predictive machine learning that would give an indication of whether a person would have a liver problem or not.

Now, as a data scientist, your goal is to build a logistic machine learning model that predicts whether a patient is healthy (non-liver patient) or ill (liver patient) based on some clinical and demographic features (or input variables) listed in the 'Data Description' section.

About the dataset
This data set contains liver patient records and non liver patient records collected from North East of Andhra Pradesh, India. The "Liver_Problem" column is the target variable used to divide groups into liver patient ( Liver_Problem == 1) or not ( Liver_Problem == 2).
Liver_Problem == 1, implies the individual is a liver patient
Liver_Problem == 2, implies the individual is not a liver patient

Data Description:
Age of the patient
Gender of the patient
Total Bilirubin
Direct Bilirubin
Alkaline Phosphotase
Alamine Aminotransferase
Aspartate Aminotransferase
Total Proteins
Albumin
Albumin and Globulin Ratio
"Liver_Problem" column is the target variable used to divide groups into liver patient (liver disease) or not (no disease).