1) The document discusses using data mining classification algorithms to identify the type of liver disease from patient data.
2) It evaluates the performance of four algorithms: First Order Inductive Learner (FOIL), Classification Based on Association (CBA), Classification based on Multiple Association Rules (CMAR), and Classification based on Predictive Association Rules (CPAR).
3) The data collected from patients includes liver function tests, other health factors like diabetes and obesity, alcohol consumption, and the diagnosed disease class. This data undergoes preprocessing to reduce dimensions before model building.