Learning curves for the modeling of sugar cane productivity
Predicting the final yield of a crop is one of the most important aspects of a mill's agricultural planning. However, numerous factors must be considered to ensure a realistic forecast. Data mining techniques are capable of generating models that predict these values by relating a large amount...
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| Main Authors: | , , , |
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| Format: | Online |
| Language: | English |
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Universidade Estadual de Campinas
2019
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| Subjects: | |
| Online Access: | https://econtents.sbu.unicamp.br/eventos/index.php/pibic/article/view/1368 |
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| Summary: | Predicting the final yield of a crop is one of the most important aspects of a mill's agricultural planning. However, numerous factors must be considered to ensure a realistic forecast. Data mining techniques are capable of generating models that predict these values by relating a large amount of data. In this project, we studied learning curves, a tool used in the analysis of a model's performance according to the amount of data available. In an analysis of a database for a sugarcane production, we compared three different modeling techniques, suitable for regression models in the prediction of the final productivity. |
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| ISSN: | 2596-1969 |
