Agricultural Crop Yield Prediction Using Machine Learning
Crop yield prediction is addressed through machine learning. Two predictor variables were used: hectares harvested, and production in tons. For the first case, the best model was a dense neural network (DNN) architecture, with a MSE of 0.0081, followed by Random Forest (RF) with an MSE of 0.0104, de...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | Spanish |
| Published: |
Fundación Koinonia
2020-10-01
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| Series: | Revista Arbitrada Interdisciplinaria Koinonía |
| Subjects: | |
| Online Access: | https://fundacionkoinonia.com.ve/ojs/index.php/revistakoinonia/article/view/1013 |