forecast_transfer: 3 tools.
| Tool | What it does | Notes |
|---|---|---|
forecast_update | Trains on the history, scores that model on the new observations it never saw (an honest out-of-sample check), then appends them to the stored series without retraining and forecasts h periods from the new end with the original conformal intervals. | |
forecast_transfer | Trains models on source series (data or y) and forecasts different target series with them (transfer learning: a new ticker, product or market with short history), with conformal intervals adapted to the targets by recalibration, error or scale ratios, or density-ratio reweighting. | |
forecast_density_ratio | Density-ratio weights w(x) = p_target(x) / p_source(x) for every source row, from a classifier trained to tell target rows from source rows on standardized features: how representative each past observation is of the target conditions. |
fincept_describe_tool.