Naïve Forecasting: A Tool to Compare Forecast Models

In this study, a freshly fitted forecast model is put up against standard procedure for comparison. But first, the essay makes distinction between confusing notion of prediction model's accuracy measure and comparison models in terms gauging their relative absolute measures various scenarios. A by itself does not give complete picture how much better newly than other benchmark built from same dataset. This article illustrates multiple regression as novel fit with naive forecasting methodology, well-known area, using cross-validation techniques. The performance was assessed two generally used measures, Mean Absolute Error (MAE) Percentage (MAPE). It discovered that performs technique both MAE MAPE. meant worthy fit. summary, it crucial to compare developed evaluate its accurately. process allows identification most suitable method specific context promotes development improved techniques comparing future.