| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| 4.86 MB | Adobe PDF |
Authors
Advisor(s)
Abstract(s)
The agricultural sector worldwide has an economic dimension related to the remuneration of the production factors applied in the sector, an environmental contribution associated with the sustainability of rural places and a social dimension related to the employment creation and the consequent level of remuneration of the labour. The question here is about the level of wages paid in the agricultural sector across the European Union countries and about the main factors that may be taken into account to predict the level of these wages paid to agricultural workers. This research intends to select the models with better precision to predict the wages paid in the European Union agriculture and to suggest important predictors from the enormous number of indicators that may be identified in the farms. The findings obtained may be considered relevant support for the design of social and agricultural policies in the European framework.
Description
Keywords
Artificial intelligence Farm accountancy data network European Union
Citation
Martinho, V.J.P.D. (2024). Machine Learning Methodologies, Wages Paid and the Most Relevant Predictors. In: Machine Learning Approaches for Evaluating Statistical Information in the Agricultural Sector. SpringerBriefs in Applied Sciences and Technology. Springer, Cham. https://doi.org/10.1007/978-3-031-54608-2_8
Publisher
Springer, Cham