This interactive tool would let users upload a dataset and instantly compare its performance across the four key benchmark methods mentioned in the "Forecaster's Toolbox" (Chapter 5):
Forecasts are equal to the value of the last observation. Forecasting: Principles and Practice
Include interactive plots that show how parameters like the "smoothing rate" in Exponential Smoothing change the forecast line in real-time. Implementation Resources You can build this using the following tools and libraries: Forecasting: Principles and Practice (3rd ed) - OTexts This interactive tool would let users upload a
Use STL decomposition (Seasonal-Trend decomposition using LOESS) to break down the user's data into Trend, Seasonality, and Remainder components. Display a leaderboard using the book's recommended error
Display a leaderboard using the book's recommended error metrics like MAE (Mean Absolute Error) and RMSE (Root Mean Squared Error) to identify which benchmark is hardest to beat.