98.7% better on seasonal, 9.8% worse on a random walk: the most useful benchmark I ran
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Before pointing Google's TimesFM 3.0 at anything real, I ran a calibration baseline. Two synthetic series with known properties, same model, same settings, held out. Seasonal with drift: 98.7% better than the naive baseline, 100% direction accuracy. Random walk: 9.8% worse than naive, 47% direction…
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- 2026-09-26 12:29 · DEV Community — Machine Learning
98.7% better on seasonal, 9.8% worse on a random walk: the most useful benchmark I ran