Summary: This dataset includes important attributes of the garment manufacturing process and the productivity of the employees which had been collected manually and also been validated by the industry experts.
| Parameter | Value |
|---|---|
| Name | Productivity Prediction of Garment Employees |
| Labeled | Yes |
| Time Series | No |
| Simulation | No |
| Missing Values | Yes |
| Dataset Characteristics | Multivariate |
| Feature Type | Integer, Real |
| Associated Tasks | Classification, Regression |
| Number of Instances | 1197 |
| Number of Features | 14 |
| Date Donated | 2020-08-02 |
| Source | UCI Machine Learning Repository |
The Garment Industry is one of the key examples of the industrial globalization of this modern era. It is a highly labour-intensive industry with lots of manual processes. Satisfying the huge global demand for garment products is mostly dependent on the production and delivery performance of the employees in the garment manufacturing companies. So, it is highly desirable among the decision makers in the garments industry to track, analyse and predict the productivity performance of the working teams in their factories. This dataset can be used for regression purpose by predicting the productivity range (0-1) or for classification purpose by transforming the productivity range (0-1) into different classes.
Garment industry, Employee productivity, Manufacturing process, Workforce analytics, Performance prediction