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Copilot/push to bmo c2 - #208
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minaattari wants to merge 34 commits into
Closed
minaattari wants to merge 34 commits into
minaattari wants to merge 34 commits into
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merge updates from vector
Add XGBoost predictor for manufacturing stress forecasts
feat(manufacturing): add notebook workbench and cached LLMP backtest
Expand manufacturing stress data features
…tput Fix/manufacturing agent json output
FRED now truncates BAMLH0A0HYM2 (ICE BofA HY OAS) to a rolling 3-year window, which silently zeroed out every fit-at-origin training example for the logistic/XGBoost/agent predictors across both backtest windows (build_feature_snapshot requires all features present or drops the row). Replace it with BAA10Y (Moody's Baa corporate yield minus 10Y Treasury), which has full history back to 1986, and rename HY_SPREAD to CREDIT_SPREAD throughout to reflect the new source. Also removes the GSCPI data source and its test, and finishes the STATISTICAL_FEATURE_SERIES_IDS -> FEATURE_SERIES_IDS cleanup in the logistic/XGBoost predictors.
Lets the tune/confirm sweep test alternative stress-label definitions (e.g. -1.5% trailing 3-month IPMAN decline instead of the -2.0% default) without editing code. Threshold changes redefine the target, so results across different thresholds are not directly comparable.
Fix manufacturing-stress credit spread feature (FRED truncation)
Improve adaptive-agent structured response handling and document the paired Lite/Advanced evaluation outputs. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Include remaining notebook updates and generated adaptive-agent and all-model report packages. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
…on history Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Backtesting lives in the adaptive model comparison notebook. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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1- sweep additional classical methods tuning and improve
2- add hybrid anchor agent
3- add adaptive agent
4- add Langfuse reports export for adaptive agent rationale tracking
4- compare all methods
5- compare adaptive agent based on LLM lite vs advanced
6- add data analysis