
Chloro: Optimizing Random Forest Regression Model for Accurate Forecasting of Days to Harvest in Hydroponic Lettuce Cultivation
This study developed a system that forecasts the days to harvest hydroponically grown lettuce by optimizing the Random Forest Regressor model, which analyzes patterns in nutrient conditions, namely pH level, Total Dissolved Solids (TDS), air temperature, and relative humidity.
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