Time Series
Data with an order, where the usual habits of splitting and shuffling quietly break.
3 articles, newest first.
- Seasonality, holidays and the calendar features that earn their place Most time series move on a calendar, not a trend. Which calendar features actually help, why one-hot day-of-week is usually wrong, and the holidays that break every model.
- Backtesting a forecast honestly Rolling-origin evaluation, the baselines a forecast must beat, and the quiet ways a backtest ends up scoring information the model would never have had.
- Time series forecasting: the five classic self-deceptions Random splits, ignored baselines, leaking features, log-space metrics, and one-step myopia — the mistakes that make forecasts look better than they are.