Markov Chains, Computer Science, Programming, Probability, Problem Solving.
plt.ylabel('Value') plt.legend() plt.show() return y_pred def prophet_predictor(self): # Prepare the data for Prophet df = pd.DataFrame({'ds': range(len(self.numericData)), 'y': self.numericData}) # Create and fit the Prophet model model = Prophet() model.fit(df) # Make future dataframe for