Create time_series_forecasting.py

src/ai/time_series_forecasting.py

@@ -0,0 +1,29 @@
+import pandas as pd
+from statsmodels.tsa.arima.model import ARIMA
+import matplotlib.pyplot as plt
+
+class TimeSeriesForecasting:
+    def __init__(self, data):
+        self.data = data
+
+    def fit_model(self, order=(1, 1, 1)):
+        """Fit the ARIMA model to the data."""
+        self model = ARIMA(self.data, order=order)
+        self.model_fit = self.model.fit()
+
+    def forecast(self, steps=5):
+        """Forecast future values."""
+        forecasted_values = self.model_fit.forecast(steps=steps)
+        return forecasted_values
+
+    def plot_forecast(self, steps=5):
+        """Plot the forecasted values along with the original data."""
+        forecasted_values = self.forecast(steps)
+        plt.figure(figsize=(12, 6))
+        plt.plot(self.data, label='Historical Data')
+        plt.plot(range(len(self.data), len(self.data) + steps), forecasted_values, label='Forecasted Values', color='red')
+        plt.title('Time Series Forecasting')
+        plt.xlabel('Time')
+        plt.ylabel('Values')
+        plt.legend()
+        plt.show()