Random forest regression for fuzzy grades

The used dataset contained information about:

• students' gender (1 = male, 2 = female);
• schools' type (1 = scientific lyceums, 2 = other lyceums, 3 = technical schools, 4 = vocational schools);
• schools' macreregion (1 = Northwester Italy, 2 = Northeastern Italy, 3 = Central Italy, 4 = Southern Italy, 5 = Southern Italy and Isles);
• students' origin (1 = native Italian student, 2 = first-generation immigrant student, 3 = second-generation immigrant student);
• students' ESCS (continuous data);
• teacher-given grades in mathematics (from 1 to 10);
• students' achievements on the INVALSI mathematics test (continuous data);
• students' fuzzy grade, obtained as a combination of teacher-given grades and achievements in mathematics (from 1 to 10).