Random forest regression for fuzzy grades
<p>The used dataset contained information about:</p> <ul> <li>students' gender (1 = male, 2 = female);</li> <li>schools' type (1 = scientific lyceums, 2 = other lyceums, 3 = technical schools, 4 = vocational schools);</li> <li>schools' macreregion (1 = Northwester Italy, 2 = Northeastern Italy, 3 = Central Italy, 4 = Southern Italy, 5 = Southern Italy and Isles);</li> <li>students' origin (1 = native Italian student, 2 = first-generation immigrant student, 3 = second-generation immigrant student);</li> <li>students' ESCS (continuous data);</li> <li>teacher-given grades in mathematics (from 1 to 10);</li> <li>students' achievements on the INVALSI mathematics test (continuous data);</li> <li>students' fuzzy grade, obtained as a combination of teacher-given grades and achievements in mathematics (from 1 to 10).</li> </ul>
ShareScore
44/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 20
- Reuse readiness
- 8
- Engagement
- 4