- Added bulk read/write methods for feature caches in IFeaturesView and its implementations to optimize performance.
- Introduced LabelCacheInvalidateAll method to manage label cache invalidation alongside feature cache.
- Implemented PooledIndependentBars method in topology interfaces to account for additional independent observations.
- Enhanced risk budget management with throttling for peak-equity updates to reduce unnecessary file operations.
- Improved error handling and logging for ATR trailing stops to ensure better visibility of issues.
- Updated alt-data handling to prevent unnecessary operations during testing and optimization phases.
~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>
The capacity budget is stated in weights per INDEPENDENT observation
and divides by the mean label lifespan to get there. It never once
did: EstimatedInSampleBars() deflates via m_labelOverlap, but it is
only ever called from InitNeuralNetwork, where the label cache does
not exist yet (that same function sets m_labelCachePrebuilt = false
a few lines below), so MeanLifespan() returned its "nothing measured"
default of 1.0 at every call. Every fresh model was sized as though
its labels did not overlap - over-budgeting the first dense layer by
a factor of L, which is several rungs of a power-of-two ladder. The
"expect overfitting, reduce the feature set or pool instruments"
warning is the branch that should fire on H1 and structurally could
not.
Fixed at the source rather than by reordering the boot sequence (the
prebuild is chunked across Train() calls and cannot complete inside
init): MeasureSwingGeometry() walks the ZigZag ONCE at init and
answers both questions from it - the median leg gives the window,
and the leg series gives the mean label lifespan analytically.
SwingPivotDirectionLabel resolves bar i when the SECOND pivot after
it commits, so a bar d bars before pivot P waits d + (the leg
leaving P); summed over every bar of every leg that is exactly the
mean the label walk accumulates.
That also closes the coherence gap the swing target opened: the
window was measured with a private +/-12-bar fractal while the label
aimed at ZigZag(12,5,3) pivots, so it was sized against a leg
distribution the label never used. One pivot source now, the
label's.
Also:
- ResetWeights() re-derives the shape. It rebuilt from the members a
history-starved init had pinned and re-saved them - so the "let
history download, then reset from the panel" advice in both
fallback warnings did nothing at all.
- The CAPACITY line prints the measured lifespan beside the one the
topology was sized for, and warns when they differ by more than a
ladder rung. That is the check that makes the estimator falsifiable.
- Topology reads the view's symbol, not _Symbol (latent for pooling).
- Unmeasured geometry defaults to HISTORY_BARS_FALLBACK, never 1.0:
under-sizing is recoverable, over-sizing silently is not.
Compile: 0 errors, 0 warnings (stage).
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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>
TARGET_SWING: the direction models learn which way the next CONFIRMED SWING
PIVOT lies from the current close. Geometry-free - the label owes nothing to a
stop, target or horizon - which is what lets trade management be tuned
separately instead of being baked into what the net learns.
SwingPivotDirectionLabel reuses the ZigZag pivot the horizon and leg-size
measurement already walk, so there is ONE notion of "pivot" in the codebase. It
walks forward in time and stops at m_swingConfirmationBars: a pivot nearer than
that is still repainting, so its label is not knowable yet and the bar stays
Neutral. That boundary is the whole lookahead control for this target.
TrainingTarget input is back (TARGET_BARRIER default, unchanged behaviour) with
TARGET_FRACTAL and TARGET_SWING beside it; |TGT:SWG1 joins the fingerprint so
switching trains a separate model rather than relabelling an existing one.
ADZigZag was renamed to ZigZag throughout (30 identifiers). It has loaded
MetaTrader's stock Examples\ZigZag at its stock defaults for some time - the
migration was done, only the name was left behind, and a name that says "AD"
about a stock indicator is exactly the legacy pointer this codebase should not
carry. No behaviour change: same #resource, same params.
Compile-verified in the staging copy: 0 errors, 0 warnings.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
RSI, MACD, Ichimoku and the five AD/Wyckoff indicators (CumulativeDelta,
ShorteningOfThrust, WyckoffEventStream, WyckoffFailedStructure,
WyckoffSignificantBarInversion). All eight inputs shipped false and each carries a
closed verdict: the three oscillators are the same patterns that measured at chance
as entries, and the Wyckoff family returned zero out-of-sample on five independent
instruments - which is what closed the context score.
RETRAIN-NEUTRAL, and this one is worth stating precisely because the change looks
larger than it is. Every removed group contributed `flag ? N : 0` to the input
width, and every flag was false, so the width was ALREADY zero for all eight: no
.nnw's input layer changes. On the fingerprints, UseRSI and the five AD flags were
hashed unconditionally and become literal 0 legacy slots (the convention the
m_focalGamma slot above them already uses); UseMACD/UseIchimoku were appended only
when enabled, so their segments simply never appear - byte-identical to every
fingerprint ever produced, since neither ever shipped on.
CADIndicatorTuner IS DELIBERATELY NOT SHRUNK. Its flat parameter array is persisted
inside every .nnw, and Unflatten() rejects a size mismatch by falling back to
constructor defaults - so dropping the dead fields would silently revert the tuned
MA period of every model on disk while keeping its trained weights. That is the
feature/weight mismatch this project has already paid for twice, and it is not
worth 200 lines. AD_TUNE_PARAM_COUNT stays 42, the dead slots are still written and
read, and AutoTune's ParamOwner gate now matches only owner 5 (MA) so nothing
searches them. The class comment says all of this at the declaration.
Also renamed ReInitADIndicators -> ReInitTunableIndicators: it rebuilds exactly one
indicator now, and a name saying "AD" for the MA handle is the kind of stale label
that gets believed later. Its release-AFTER-recreate ordering is untouched - that
is a documented fix, not bookkeeping.
Compile-verified in the stage copy: 0 errors, 0 warnings, against the same 0/0
baseline.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Expert/AIBase/Features.mqh (2017 lines, 38 methods) split by exclusivity grep
(whole-repo, not just Expert/): 30 methods -> Expert/Features/FeatureBuilder.mqh
(CFeatureBuilder + CFeaturesView/CAIBaseFeaturesView), 8 stay behind as a much
smaller raw partial.
CFeatureBuilder is STATEFUL, same shape as Excursion/OnlineLearning: owns the
10 feature-only indicator handles (m_Volumes/m_MA/m_RSI/m_MACDFeature/
m_Ichimoku/5 AD* CiCustom indicators - grep-verified touched nowhere else in
the repo, only their bare declarations) plus the depth-probe/handle-repair/
spread-series/detectability-latch scalars (exclusive, Lifecycle.mqh ctor-init
only elsewhere). m_Open/m_Close/m_High/m_Low/m_Time/m_ATR/m_ADZigZag stay
signal-owned - Labels.mqh/AutoTune.mqh/Training.mqh read them directly - and
are reached read-only through the view (FeatureOpenAt/FeatureHighAt/
FeatureLowAt/ChartBarClose/ChartBarTime/OnlineAtrMain, all reused where a
forward already existed).
Deliberately did NOT move InitOpen/InitClose/InitHigh/InitLow/InitTime/
InitADZigZag/ResizeBuffers/RefreshData: they manage the 7 shared indicators'
Create/BufferResize/Refresh lifecycle, which would need a pure-relay wrapper
per operation per indicator for zero coupling benefit - same judgment as
Topology's boot sequence. They stay in Expert/AIBase/Features.mqh and reach
CFeatureBuilder's 10 owned indicators through 20 new Feature*BufferResize()/
Feature*Refresh() forwards (signal calling into its own owned collaborator
directly, no view needed in that direction).
Whole-repo grep (not just Expert/) caught a real external miss the campaign's
own doctrine warns about: Signals/SignalMETA.mqh read m_spreadSeries/
m_spreadSeriesBars directly as an inherited protected field (a subclass, not
an AIBase/*.mqh partial) - fixed with two new FeatureSpreadSeriesBars()/
FeatureSpreadSeriesAt() forwards.
Verified: if(/for(/while( counts identical between the original file and the
new split (269/20/1); return-count delta (+12) fully accounted for by the 12
new trivial one-line forwards added (10 indicator BufferResize + 2 spread-
series getters); quoted-string-literal diff empty except two doc-comment
paraphrases. Self-compiled 0 errors, 0 warnings.
