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QUESTION 4 An analyst ran three models as follows with the respective training and validation periods error values: 1. Linear Trend; Training Period RMSE =600.56, Validation Period RMSE = 502.35 2. Exponential Trend + Seasonality: Training Period RMSE = 586.25, Validation Period RMSE = 555.24 3. Polynomial Trend + Seasonality: Training Period RMSE = 502.69, Validation Period RMSE =70460.25 Based on the above information, please select the right statements below. a. An overfitting issue is present in the exponential trend + seasonality model. b. The exponential trend + Seasonality model has learned the systematic components better than others c. The polynomial trend + Seasonality model can forecast better than others O d. The exponential trend + Seasonality model can forecast better than other models. O e. An overfitting issue is present in the polynomial trend + seasonality model.

QUESTION 4 An analyst ran three models as follows with the respective training and validation periods error values: 1. Linear Trend; Training Period RMSE =600.56, Validation Period RMSE = 502.35 2. Exponential Trend + Seasonality: Training Period RMSE = 586.25, Validation Period RMSE = 555.24 3. Polynomial Trend + Seasonality: Training Period RMSE = 502.69, Validation Period RMSE =70460.25 Based on the above information, please select the right statements below. a. An overfitting issue is present in the exponential trend + seasonality model. b. The exponential trend + Seasonality model has learned the systematic components better than others c. The polynomial trend + Seasonality model can forecast better than others O d. The exponential trend + Seasonality model can forecast better than other models. O e. An overfitting issue is present in the polynomial trend + seasonality model.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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QUESTION 4 An analyst ran three models as follows with the respective training and validation periods error values: 1. Linear Trend; Training Period RMSE =600.56, Validation Period RMSE = 502.35 2. Exponential Trend + Seasonality: Training Period RMSE = 586.25, Validation Period RMSE = 555.24 3. Polynomial Trend + Seasonality: Training Period RMSE = 502.69, Validation Period RMSE =70460.25 Based on the above information, please select the right statements below. a. An overfitting issue is present in the exponential trend + seasonality model. b. The exponential trend + Seasonality model has learned the systematic components better than others c. The polynomial trend + Seasonality model can forecast better than others O d. The exponential trend + Seasonality model can forecast better than other models. O e. An overfitting issue is present in the polynomial trend + seasonality model.
Transcribed Image Text:QUESTION 4 An analyst ran three models as follows with the respective training and validation periods error values: 1. Linear Trend; Training Period RMSE =600.56, Validation Period RMSE = 502.35 2. Exponential Trend + Seasonality: Training Period RMSE = 586.25, Validation Period RMSE = 555.24 3. Polynomial Trend + Seasonality: Training Period RMSE = 502.69, Validation Period RMSE =70460.25 Based on the above information, please select the right statements below. a. An overfitting issue is present in the exponential trend + seasonality model. b. The exponential trend + Seasonality model has learned the systematic components better than others c. The polynomial trend + Seasonality model can forecast better than others O d. The exponential trend + Seasonality model can forecast better than other models. O e. An overfitting issue is present in the polynomial trend + seasonality model.
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