Commit graph Warrior_EA/Expert/OnlineLearning/AIBaseOnlineLearningViewImpl.mqh
Author SHA1 Message Date
AnimateDread
1baa13c5b4 refactor(meta): remove meta-labeling entirely - RETRAIN-NEUTRAL
~2,300 lines. META had real, repeatedly measured ranking skill and ZERO
operating points that ever cleared break-even (0/350 H1 eras, 1/999 H4
pre-2-sigma, 0/8 pooled fitted points). The clinching arithmetic was edge x
width = 0.095 ATR/trade against spread 0.099 ATR/trade, and the
dose-response showed the high-conviction tail is temporally unstable -
the precision-vs-threshold slope flips sign between calib and test on 3 of
4 symbols, so no ex-ante threshold rule exists. It shipped default-off and
never gated a live entry. The self-measured tier weights are what actually
rank the vote, and all six H4 instruments converged on them alone.

RETRAIN-NEUTRAL, and that is the property that made this safe:

  - The weights fingerprint emitted "|TGT:META2" or "|TGT:SWG1" from an
    if/else. Every direction model already took the SWG1 arm, so
    collapsing it to an unconditional append is byte-identical. No .nnw or
    .cfg is orphaned or re-keyed.
  - NetInputWidth() lost its "+ MetaDescWidth()" term. MetaDescWidth()
    returned 0 for every direction model, so the input layer is unchanged.
  - DbLegacyAiSlot()'s slot 5 was reachable only with all four Use_* NNs
    off AND meta on - a config that never shipped. Every existing .db keeps
    its filename.

Deleted outright: Signals/SignalMETA.mqh, Expert/Trading/MetaGate.mqh (the
directory is now empty), Expert/Training/{MetaCorpus,MetaCandidateStore,
MetaFamilies}.mqh, Tests/Test_MetaFamilies.mq5, Meta_Labeling_Design.md.

Unwound in place, the delicate part: Training.mqh carried four
IsMetaTarget() branches whose else-arm WRAPPED the direction body (pass 1
queueing, pass 2 backprop, pass 2.5 calibration, pass 3 OOS scoring). Each
wrapper is removed and the direction body promoted back to its original
nesting - the bodies were never re-indented when the wrappers were added,
so the promoted code is byte-identical to what ran before META existed.
Also gone: the ensemble verdict's meta-veto replay and its
approved/vetoed/unscored counters, the per-family/per-side OOS
decomposition arrays, the m_isTrainQueueCand parallel queue and its
lockstep shuffle, and the S2 era report.

Also removed: the CMetaGate abstraction and the live CheckOpenPosition
veto; m_gates plus AddFilter's non-voter routing and IsVotingSignal()
(META was the only non-voting child, so m_gates was always empty);
m_parentSignal/SetParentSignal (existed only to reach the root's gate);
SweepPrepare/SweepPrepareIndicator (only caller was the corpus sweep);
IsMetaTarget() from all four view interfaces and their adapters;
Use_MetaLabeling, EnableMETA, Meta_ExportDataset, m_trainTarget.

EvalShift is KEPT - HistoricalNetVote() uses it for the filtered overlay,
not just the corpus sweep; only its comment changed. The 2-output softmax
arm in NetForward.mqh is kept too: it costs nothing and is the reusable
binary-head path, now commented as unclaimed rather than as META's.

Compile-verified in _claude_stage: 0 errors, 0 warnings, matching the
pre-edit baseline.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-08-25 09:44:52 -04:00
AnimateDread
8f2164698b feat(target): delete the barrier/geometry stack - the label is the verdict
Step 3 of the swing-pivot plan, whole-hog. The swing label is now the ONE
target and the era verdict is precision + recall per class against the
label's own base rate - no win rate, no break-even, no expectancy, no
geometry anywhere in training.

DELETED
- Expert/Excursion/ (4), Expert/BarrierHorizon/ (4), GeometrySweep,
  FirstPassageLadder, Labeling/TripleBarrier.mqh (CLabelOverlap survives
  in Labeling/LabelOverlap.mqh), 3 test EAs.
- TripleBarrierLabel + walk, fractal label, geometry derivation/scan/
  adoption, exit-policy replay, excursion MI targets, the drift verdict
  (DIRECTION_INTELLIGENT), the recall floor, balanced-accuracy telemetry,
  the barrier defines, the .cfg geometry adopt (slots kept as zeros for
  the positional layout), the derived-geometry live-order override.
- TRAINING_TARGET input/enum: direction models are always swing; META2
  re-keys the meta head onto label agreement (descriptor loses its two
  geometry slots).

REWORKED
- Labels.mqh (1795 -> ~370 lines): AdvanceSwingLabelState with
  FINALITY-GATED CACHING - an unresolved bar (pivot pair uncommitted) is
  never cached, so it can never freeze as a false Neutral; training,
  calibration, OOS scoring and online learning all skip unresolved bars.
- SDeployVerdict: significance-only; SOosTally chance = larger
  directional class share; pooled gate poolability = timeframe (record v2).
- Purge/embargo/declustering gaps: the measured mean label resolution
  lag (LabelResolutionBars), not a barrier horizon.
- Pool purge key + backfill DB rows: marked at the bar the label
  resolved on (m_labelResolveAge), not a fabricated barrier touch.
- Online learning frontier: finality, not a horizon delay.
- m_bestBalancedOos -> m_bestSelectionScore, m_erasSinceBestBalanced ->
  m_erasSinceBest, ensemble vote outcome arrays -> label arrays.

STEP 4 folded in: Entry_Multiplier / SL_Mode / TP_Mode / tradingdirection
are inputs again - trade management is the tester GA's search space.

Fingerprints: every direction model re-keys (TGT:SWG1 now unconditional,
CUT token gone); META1 -> META2. Full retrain, as planned.

Compile-verified in _claude_stage: Warrior_EA + both surviving test EAs,
0 errors, 0 warnings each.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-08-24 20:42:31 -04:00
AnimateDread
78a070eb5c refactor(online-learning): OnlineLearning is a real collaborator, not a raw-include partial (S5)
Expert\AIBase\OnlineLearning.mqh (595 lines) -> Expert\OnlineLearning\:
IOnlineLearningView.mqh (abstract, ~50 accessors) + AIBaseOnlineLearningView.mqh/
AIBaseOnlineLearningViewImpl.mqh (the adapter) + OnlineLearning.mqh (COnlineLearning).

STATEFUL, unlike CModelPersistence: grep-verified the shadow net, the OOS
continual-learning simulation state and the pattern-database backfill state are
genuinely exclusive to this file's own methods - Training.mqh/Topology.mqh/
Lifecycle.mqh/the signal's own header only ever CHECKED or RESET this state at
era/lifecycle boundaries, never owned it, so it moved onto the collaborator as
real members (same doctrine as Excursion). Those external touch points became
consolidated view/forward calls instead of raw field pokes - AbortSimIfActive()
replaces THREE separate copies of the same delete/null/false triple (Training.mqh's
stop path, FlushTrainRun, ResetWeights), matching the geometry-scan duplicate-reset
precedent in project memory. ResetForFreshTopology() replaces Topology.mqh's five-
field reset block, DeployNet() replaces the shadow-preferred net selection duplicated
in Inference.mqh and ChartScoreBarForRescan, and BlendTowardNet() replaces the era-end
blend Training.mqh used to poke m_shadowNet for directly.

Reused the signal's existing Data*()/Chart*()/Persist*() getters wherever one already
answered the question (labels/outcome/history/horizon/priors/servable-bars/etc.);
added ~30 new Online*() wrappers only for what nothing else exposed yet. The three
PersistOnline*() get/set pairs (WST3 .stats fields) now forward through the owning
member instead of touching the field directly - CModelPersistence is unaffected.
Every method body is a pure relocation of the original's statements in original
order; verified against `git show HEAD~1:Expert/AIBase/Excursion.mqh`-style diff
against the pre-extraction file kept in the working tree until this commit.

Compiled 0 errors, 0 warnings (stage mirror + MetaEditor64 /compile, ~91s).

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-08-23 22:59:02 -04:00