Which of the following is the right option to compute the Root mean squared error (RMSE) of the forecasting model?Answer choicesSelect only one optionREVISITrmse_test=mean_squared_error(df_test['demand'],df_test['Predicted'],squared=True)rmse_test=mean_squared_error(df_test['demand'],df_test['Predicted'])rmse_test=mean_squared_error(df_test['demand'],df_test['Predicted'],squared=False)rmse_test=mean_squared_error(df_test['demand'],df_test['Predicted'],square=False)

Which of the following statements is correct about our RMSE?An RMSE of 0.0881 indicates a perfect fit of the model to the training data.An RMSE value of 0.0881 suggests that, at most, the predicted values deviate by approximately 0.08 units from the actual values.An RMSE of 0.0881 suggests that, on average, the predicted values are off by approximately 0.0881 unitsAn RMSE of 0.0881 suggests that the predicted values are correct 8.81% of the time.

Which of the following is a correct implementation of mean squared error (MSE) metric?Note: numpy library has been imported as np.def MSE(real_target, predicted_target):return np.mean((np.square(real_target) – np.square(predicted_target)))def MSE(real_target, predicted_target):return np.mean((real_target – predicted_target)**2)def MSE(real_target, predicted_target):return np.sqrt(np.mean((np.square(real_target) – np.square(predicted_target))))None of the above

Implementation of mean squared error (MSE) metricWhich of the following is a correct implementation of mean squared error (MSE) metric?Note: numpy library has been imported as np.def MSE(real_target, predicted_target):return np.mean((np.square(real_target) – np.square(predicted_target)))def MSE(real_target, predicted_target):return np.mean((real_target – predicted_target)**2)def MSE(real_target, predicted_target):return np.sqrt(np.mean((np.square(real_target) – np.square(predicted_target))))None of the above

Which of the following is called Standard Error? T-statistic squared Square root of SSE Square root of SST Square root of MSE

Which of the following models will you choose for forecasting the sales of the mobile phone?Model 1 with RMSE 2.33e+02Model 2 with RMSE 0.235e+03Model 3 with RMSE 2.32+e03Model 4 with RMSE 2.33e+05Answer choicesSelect only one optionREVISITModel 3Model 2Model 1Model 4