The NN now has a target that is not per-bar direction (closed, best-of-999
p=1.0000): P(win | this journaled candidate, at the EA's own SL/TP, net of
cost). One net for all 52 pattern-sides, AIType=AI_META.
- NetForward.mqh: the host-side softmax+CE gradient generalized total==3 ->
2||3 on both backprop paths; a 2-class softmax IS a logistic head, and no
compute backend changes.
- SignalMETA.mqh (new): corpus loaded read-only from the LARGEST signal DB on
disk (decoupled from the config fingerprint that burned four S1 runs); the
GMT->server offset is measured PER ROW against entryPrice vs bar open
(DST-immune, histogram logged); a window-span regime filter drops the
pre-2017 daily-backfill rows; 31-feature setup descriptor appended at the
input (26 one-hot + side + tanh netVote + SL/TP ATR + spread/ATR).
- Training.mqh: candidate-queued pass 1, binary-target pass 2, per-candidate
calibration (2.5) and OOS (3) walks. Counter mapping win->Buy / loss->Sell
lets checkpoint selection, the edge floor, the plateau ladder and the
family-wise deploy gate run UNCHANGED: precision reads as win rate among
traded candidates, chance as the base win rate, recalls as sensitivity/
specificity. Era-end META line: coverage x (p - break-even) vs the null.
- Labels are the side-conditional triple-barrier win caches - never the DB's
stop-and-reverse outcome. Logit adjustment deliberately skipped (~40% base
rate). Live inference + online learning guarded off until S3.
- Fingerprint: conditional |TGT:META1; State\META\ folder + 2-output filename
slot keep meta models fully separate from direction models.
Compiles clean (0 errors, 0 warnings). S2 run = attach a chart with
AIType=AI_META; S3 wires the votes via the per-side hooks.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Every removal below is FINGERPRINT-NEUTRAL by construction: each retired
input is pinned to the exact value it already shipped with, so running
models keep their filenames and resume rather than restarting at era 0.
Verified field by field against BuildConfigFingerprint.
Removed as inputs, kept as pinned constants (the value was never a
preference the user had a basis to change):
- OutputNeuronsCount. The regression head predicts a continuous quantity
the triple-barrier label does not contain; the target is an EVENT, so
the right output is its probability. The regression code paths stay
implemented and dormant - they cost nothing and removing them would
touch every scoring path at once.
- MinRecall. A safety floor, not a preference, and the only direction a
user can move it is the harmful one: raising it past what the config
reaches yields NO model, not a better one (observed repeatedly at 60).
- SwingConfirmationBars. Stopped gating the labels with the relabel, but
is STILL load-bearing for the swing-context input features - it is the
ZigZag repainting embargo, and without it those 9 features read a leg
the live bar could not have had yet. Pinned, not deleted.
- MaxErasPerRun (runaway backstop, never reached in a healthy run),
FreezePriorCalibration (unanswerable by a user; near-balanced labels
make the priors stable anyway), VerboseMode (developer view, joins
DebuggingMode), MACD/Ichimoku periods x6 (both indicators ship
disabled, and as optimizer dimensions they are pure overfitting
surface - the AI auto-tuner is the supported way to move them).
- SignalClusterWindow -> 3, no longer an input. Barrier labels make
consecutive setups real, which argued for 0; it is not 0 because on D1+
a 6-bar window spans over a week and two arrows a day apart on a
weekly-scale move are one event. 3 splits it correctly by timeframe.
- EnableOnlineLearning -> ON. Adapting to a changing market is what keeps
a months-attached model from going stale, and the rolling-accuracy
freeze is what makes it safe. See the caveat noted in the handoff: it
had not been forward-tested on a live feed when this became default.
Removed entirely:
- Intraday Time Filter (5 inputs + Signals/SignalITF.mqh). Two of its
five inputs were raw BITMASKS, which is an implementation detail
exposed as a control. The job is covered three times over by things
that are declarative or that learn: the session filter, the
time-of-day/day-of-week input features (the network discovers which
hours are good rather than being told), and the journal's time buckets.
- Market Depth Filter (5 inputs + Signals/SignalMarketDepth.mqh, plus
its OnInit probe and OnDeinit release). It needs real level-2 data
that this broker - and most retail MT5 brokers - do not provide, so
the module has never once executed against real data. Shipping four
tuning dropdowns for an untested path is worse than shipping nothing:
the only users who could enable it would be its first-ever testers,
live. If DOM returns it should be a FEATURE fed to the network, not a
rule-based veto with hand-tuned thresholds - imbalance is data.
- IndicatorTuneTrials, replaced by ComputeTuneTrialBudget(). The useful
budget depends on how many parameters are actually being searched,
which depends on which features are enabled - so one number meant
wildly different things run to run. The shipped 32 was ~10 candidates
per dimension against one enabled indicator (wasteful: each costs
GA_SEEDS full training runs) and under one per dimension against all
nine (blind). Now population ~ 4 x active dimensions, clamped [8,64],
with CADIndicatorTuner::ActiveDimensions() defined immediately above
PerturbRandom() so the two cannot drift apart.
- Six orphaned enums (TUNE_TRIALS_PRESET, DOM_*, ENTRY_HOUR_OF_DAY,
TIME_FILTER_DAY_OF_WEEK), 81 lines.
Other UX:
- SL_ATR_x1 / TP_ATR_x3 now carry the "(classic)" default marker every
other preset enum in the file already used. Nothing in the SL/TP
dropdowns previously told a user which pair was the shipped default -
which matters far more since the relabel, because those two define the
labels and changing either forces a retrain.
- Neural Network section moved directly ABOVE AI Input Features: choose
the architecture, then choose what it sees. NN Optimizer / Performance
stays last - the Adam/Sgd inputs are declared in AI/Network.mqh and
render immediately after that divider.
- News feature + window moved to the end of the AI feature list, below
Wyckoff Bar Inversion.
- Dropped "(0-100)" from Min vote to open - it is an enum, not a number.
Both builds compile 0 errors / 0 warnings. No retrain forced.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Add MACD_FAST, MACD_SLOW, MACD_SIGNAL presets and Ichimoku Tenkan, Kijun, Senkou presets to InputEnums.mqh. All combinations are designed to satisfy the respective indicator's validation rules (fast < slow for MACD, Tenkan < Kijun < Senkou B for Ichimoku), eliminating init errors and allowing the auto-tuner to perturb settings independently.
Introduce VOTE_CLOSE_PRESETS enum with a Disabled option (value 101) that bypasses vote-driven position closing via arithmetic thresholding, removing the need for a separate boolean flag. This ensures positions exit only via stop-loss, take-profit, or trailing when disabled.
Remove verbose book references from input parameter comments in
Network.mqh for clarity. Add #ifndef guard around ENUM_OPTIMIZATION
to allow inclusion from multiple headers without redefinition.
Document the MQL5 Market DLL restriction in NeuronDirectML.mqh and
introduce WARRIOR_MARKET_BUILD macro to conditionally compile out
DirectML DLL imports for Market-compliant builds.
Audit turned up a real gap for a prop-firm-portfolio-manager use
case: nothing in this codebase watched for account-level daily-loss
or max-drawdown breaches - the single most common way a prop-firm
evaluation actually gets failed.
New Signals/SignalRiskGuard.mqh (CSignalRiskGuard), wired into the
exact same filter-composition chain as SignalNewsFilter/
SignalSessionFilter (CreateSignalWithRetry/AddFilterToSignal, no new
architecture). Vetoes new entries only (never closes existing
positions - a materially bigger behavior change, left to the
trader/EA's own SL/TP handling) once either MaxDailyLossPct or
MaxDrawdownPct (new RISK_LIMIT_PCT_PRESET inputs, both default
disabled) is breached. Peak equity and the current broker day's
starting balance persist to a small local per-symbol-per-magic state
file - peak equity in particular must survive a restart to mean
anything, otherwise a restart would silently reset drawdown tracking.
New RISK_LIMIT_PCT_PRESET enum (2/3/4/5/8/10/15/20%) rather than
reusing PERCENTAGE_PRESETS, which steps by 10 starting at 10 - too
coarse for prop-firm-style limits (commonly single-digit daily loss,
~8-10% max drawdown). Compiled clean (MetaEditor, 0 errors/0
warnings).
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
- Ensure `tick_volume` array is set as series in ADShorteningOfThrust.mq5 to prevent future-data leak in volume calculations.
- Ensure `open` array is set as series in ADWyckoffFailedStructure.mq5 to prevent future-data leak in structure detection.
- Add missing PReLU gradient scaling (multiply by 0.01 for negative outputs) in CPU_CalcHiddenGradient and DirectML shader to match expected derivative behavior across all backends.
