Forecast Errors: MAPE, sMAPE and MASE

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Unit 18 · Correlation & Forecasting0/2 to milestone

Implement three forecast accuracy metrics (as percentages for the first two):

  • mape(y, f) = 100n∑∣y−fy∣\frac{100}{n}\sum\left|\frac{y - f}{y}\right|, skipping points where y=0y = 0
  • smape(y, f) = 100n∑∣y−f∣(∣y∣+∣f∣)/2\frac{100}{n}\sum\frac{|y - f|}{(|y| + |f|)/2}, counting a term as 0 when both are 0
  • mase(y, f, y_train, m=1) = MAE of the forecast divided by the in-sample MAE of the seasonal naive forecast on y_train (lag m)
#forecasting#metrics2 visible + 1 hidden tests
solution.py · Python 3.13
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Forecast Errors: MAPE, sMAPE and MASE · TechGradify