Potato Price Prediction Model
This model predicts potato prices based on various features such as arrival quantity, temperature, humidity, and historical price data.
Input Features
- Date: Date of prediction (format: YYYY-MM-DD)
- ArrivalQuantity: Quantity of potatoes arriving at the market
- Temperature: Temperature on the given date
- Humidity: Humidity on the given date
- Wind direction: Wind direction on the given date
- Events: Any significant events on the given date
- Impacts: Any significant impacts on the given date
- PriceLag1: Previous day's price
- PriceLag7: Price from 7 days ago
- PriceRollingMean7: 7-day rolling mean price
- PriceRollingStd7: 7-day rolling standard deviation of price
- PrevWeekAvgPrice: Average price of the previous week
Output
The model returns a predicted potato price for the given input features.
Usage
from potato_price_model import predictor
input_data = {
'Date': '2024-09-14',
'ArrivalQuantity': 1000,
'Temperature': 25,
'Humidity': 60,
'Wind direction': 180,
'Events': 'Normal day',
'Impacts': 'No significant impacts',
'PriceLag1': 50,
'PriceLag7': 48,
'PriceRollingMean7': 49,
'PriceRollingStd7': 2,
'PrevWeekAvgPrice': 49
}
result = predictor.predict(input_data)
print(f"Predicted potato price: {result['predicted_price']}")
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