Time Series Forecast Evaluation Methods 📊
Learn 3 key methods to evaluate forecast accuracy in time series analysis: ACF, error distribution, and time consistency.
Data & Donuts
853 views • Dec 2, 2024
About this video
This video goes over 3 different methods for evaluating forecast accuracy for time series analysis.
First, we cover the Autocorrelation Function (ACF) plot to see if your errors are truly random. Secondly, we explore histograms to see if your model is biased and if your errors are symmetric. Finally, we look at how your errors behave over time to check for consistent error size.
Timeline:
00:00 Introduction to different tests
00:13 Autocorrelation Function Plot
02:53 Histogram of Errors
04:11 Plotting errors over time
First, we cover the Autocorrelation Function (ACF) plot to see if your errors are truly random. Secondly, we explore histograms to see if your model is biased and if your errors are symmetric. Finally, we look at how your errors behave over time to check for consistent error size.
Timeline:
00:00 Introduction to different tests
00:13 Autocorrelation Function Plot
02:53 Histogram of Errors
04:11 Plotting errors over time
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Video Information
Views
853
Likes
38
Duration
5:55
Published
Dec 2, 2024
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