Table 1 Dataset description.
From: Enhancing software effort estimation with random forest tuning and adaptive decision strategies
Dataset name | Number of projects | No. of attributes | Feature types | Target variable | Domain/source | Citation |
|---|---|---|---|---|---|---|
China | 499 | 18 | Numerical, Categorical | Effort (person-hours) | Various Industries / PROMISE Repository | PROMISE Repository30 |
Albrecht | 24 | 7 | Numerical | Effort (person-months) | IT Projects / PROMISE Repository | |
COCOMO81 | 63 | 17 | Numerical, Categorical | Effort (person-months) | NASA / PROMISE Repository | PROMISE Repository30 |
Desharnais | 81 | 13 | Numerical, Categorical | Effort (person-hours) | Canadian Software House / PROMISE Repository | |
JM1 | 10,878 (modules) | 21 | Numerical | Effort (person-hours) | NASA Software Engineering Laboratory / PROMISE Repository |
