forked from animatedread/Warrior_EA
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>
513 lines
23 KiB
MQL5
513 lines
23 KiB
MQL5
//+------------------------------------------------------------------+
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//| CustomEnums.mqh |
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//| AnimateDread |
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//| https://www.mql5.com |
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//+------------------------------------------------------------------+
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#property copyright "AnimateDread"
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#property link "https://www.mql5.com"
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//--- Weight-update optimizer. This is really an AI\Network.mqh library type; a guarded duplicate is
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//--- kept here so Variables\Inputs.mqh (which uses it for the TrainingOptimizer input) can be included
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//--- before the AI headers - putting the EA's own inputs at the top of the Inputs tab. Keep in sync
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//--- with AI\Network.mqh's copy; the shared WARRIOR_ENUM_OPTIMIZATION_DEFINED guard prevents a
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//--- duplicate definition whichever header is parsed first.
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#ifndef WARRIOR_ENUM_OPTIMIZATION_DEFINED
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#define WARRIOR_ENUM_OPTIMIZATION_DEFINED
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//--- A third DFA entry was removed 2026-07-28 - see AI\Network.mqh's copy for the full rationale (it was
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//--- a deterministic index-parity sign flip on the gradient, i.e. ascent on half of every weight tensor,
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//--- not Direct Feedback Alignment). SGD/ADAM keep ordinals 0/1: they feed the weights-filename
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//--- fingerprint and must never be renumbered.
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enum ENUM_OPTIMIZATION
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{
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SGD, // SGD + Momentum (heavy-ball, simpler, needs more eras)
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ADAM // Adam (adaptive step, faster convergence, can overfit)
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};
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#endif
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//--- Logical, commonly-used Moving Average / RSI periods only - keeps the Classic Signals inputs (and
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//--- the AutoTuneIndicators search space over them, see ADIndicatorTuner.mqh) from being set/perturbed
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//--- to an arbitrary, non-standard period.
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enum MA_PERIOD_PRESETS
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{
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MA_PERIOD_5 = 5, // 5
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MA_PERIOD_8 = 8, // 8
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MA_PERIOD_9 = 9, // 9
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MA_PERIOD_10 = 10, // 10
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MA_PERIOD_13 = 13, // 13
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MA_PERIOD_20 = 20, // 20
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MA_PERIOD_21 = 21, // 21
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MA_PERIOD_50 = 50, // 50
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MA_PERIOD_100 = 100, // 100
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MA_PERIOD_200 = 200, // 200
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};
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//--- Unified moving-average TYPE, spanning the advanced/institutional MAs AND the standard methods, all
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//--- served by the one CustomIndicators\ADMovingAverage.mq5. VALUES ARE THE INDICATOR'S OWN InpType codes
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//--- and MUST stay in sync with it: 0..4 (ALMA/DEMA/ZLEMA/T3/Kalman) are the original codes, unchanged for
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//--- cross-platform parity with the SQX build; 5..8 (SMA/EMA/SMMA/LWMA) were added on top. Drives both the
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//--- classic MA vote (Signals\SignalMA.mqh) and the NN MA input feature, and is auto-tuner-searchable.
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enum MA_TYPE_PRESETS
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{
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MA_TYPE_ALMA = 0, // ALMA (Arnaud Legoux)
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MA_TYPE_DEMA = 1, // DEMA (double exponential)
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MA_TYPE_ZLEMA = 2, // ZLEMA (zero-lag)
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MA_TYPE_T3 = 3, // T3 (Tillson)
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MA_TYPE_KALMAN = 4, // Kalman filter
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MA_TYPE_SMA = 5, // SMA (simple)
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MA_TYPE_EMA = 6, // EMA (exponential)
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MA_TYPE_SMMA = 7, // SMMA (smoothed)
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MA_TYPE_LWMA = 8, // LWMA (linear weighted)
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};
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enum RSI_PERIOD_PRESETS
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{
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RSI_PERIOD_2 = 2, // 2
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RSI_PERIOD_5 = 5, // 5
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RSI_PERIOD_7 = 7, // 7
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RSI_PERIOD_9 = 9, // 9
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RSI_PERIOD_14 = 14, // 14 (classic)
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RSI_PERIOD_21 = 21, // 21
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RSI_PERIOD_25 = 25, // 25
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};
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//--- MACD periods (Signals\SignalMACD.mqh classic vote + the MACD input feature). The preset SETS are
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//--- deliberately chosen so that EVERY fast/slow combination satisfies CSignalMACD::ValidationSettings()'s
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//--- "slow must exceed fast" rule - the fast list tops out at 15, the slow list starts at 17. A trader
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//--- picking two legal-looking values from the dropdowns can therefore never produce a combination that
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//--- fails init, and the auto-tuner (ADIndicatorTuner::PerturbRandom) can perturb either one in isolation
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//--- without having to know the other's current value.
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enum MACD_FAST_PRESETS
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{
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MACD_FAST_5 = 5, // 5
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MACD_FAST_8 = 8, // 8
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MACD_FAST_12 = 12, // 12 (classic)
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MACD_FAST_15 = 15, // 15
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};
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enum MACD_SLOW_PRESETS
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{
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MACD_SLOW_17 = 17, // 17
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MACD_SLOW_21 = 21, // 21
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MACD_SLOW_26 = 26, // 26 (classic)
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MACD_SLOW_34 = 34, // 34
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MACD_SLOW_50 = 50, // 50
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};
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enum MACD_SIGNAL_PRESETS
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{
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MACD_SIGNAL_5 = 5, // 5
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MACD_SIGNAL_7 = 7, // 7
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MACD_SIGNAL_9 = 9, // 9 (classic)
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MACD_SIGNAL_12 = 12, // 12
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};
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//--- Ichimoku periods (Signals\SignalIchimoku.mqh classic vote + the Ichimoku input feature). Same
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//--- all-combinations-are-legal design as the MACD presets above, against
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//--- CSignalIchimoku::ValidationSettings()'s "Tenkan < Kijun < Senkou B" rule: Tenkan tops out at 20,
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//--- Kijun spans 22-40, Senkou B starts at 44. The classic 9/26/52 triple is in the middle of each.
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enum ICHIMOKU_TENKAN_PRESETS
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{
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ICHI_TENKAN_7 = 7, // 7
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ICHI_TENKAN_9 = 9, // 9 (classic)
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ICHI_TENKAN_12 = 12, // 12
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ICHI_TENKAN_20 = 20, // 20
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};
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enum ICHIMOKU_KIJUN_PRESETS
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{
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ICHI_KIJUN_22 = 22, // 22
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ICHI_KIJUN_26 = 26, // 26 (classic)
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ICHI_KIJUN_30 = 30, // 30
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ICHI_KIJUN_40 = 40, // 40
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};
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enum ICHIMOKU_SENKOU_PRESETS
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{
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ICHI_SENKOU_44 = 44, // 44
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ICHI_SENKOU_52 = 52, // 52 (classic)
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ICHI_SENKOU_60 = 60, // 60
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ICHI_SENKOU_120 = 120, // 120
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};
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//--- custom enumerations for certain settings, minimizes overfitting
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enum IND_PERIODS_PRESETS
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{
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PERIOD_5 = 5, // 5 Periods
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PERIOD_10 = 10, // 10 Periods
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PERIOD_14 = 14, // 14 Periods (classic)
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PERIOD_20 = 20, // 20 Periods
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PERIOD_30 = 30, // 30 Periods
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PERIOD_50 = 50, // 50 Periods
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PERIOD_100 = 100, // 100 Periods
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PERIOD_200 = 200, // 200 Periods
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};
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enum TRAINING_YEARS_PRESET
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{
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YEARS_1 = 1, // 1 year
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YEARS_2 = 2, // 2 years
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YEARS_5 = 5, // 5 years
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YEARS_10 = 10, // 10 years
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YEARS_20 = 20, // 20 years
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};
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//--- Stop-loss sizing mode. The ATR_* presets place the SL a fixed multiple of ATR FROM THE ENTRY
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//--- PRICE. SL_INTELLIGENT uses the same entry anchor but tightens the distance as live AI/DB
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//--- confidence rises (see CExpertSignalCustom::OpenParams()'s AI_SL_TIGHTEN_FACTOR) - a
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//--- high-conviction setup gets a tighter stop, a marginal one keeps the full ATR cushion. Negative
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//--- sentinel so it can never be mistaken for a literal ATR multiple.
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//--- SWING-ANCHORED STOPS WERE REMOVED 2026-07-31. Both the ATR presets ("N ATR beyond the swing") and
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//--- SL_PREV_SWING ("exactly at the swing") keyed the stop to the recent swing high/low, which makes
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//--- the risk on a trade a function of how far away the last swing happens to sit rather than of
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//--- current volatility: a shallow pullback produced a stop tight enough to be taken out by noise on a
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//--- setup that then ran to target. Anchoring to the entry makes risk exactly N*ATR by construction,
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//--- which is also what kept the old minimum-reward:risk rejection satisfiable without depending on
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//--- swing geometry. That filter is gone (2026-08-09); the coupling is still the right shape.
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//--- The "(classic)" marker on the shipped default follows the same convention as every period preset
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//--- below. It matters more here than anywhere else in this file: since the 2026-08-01 triple-barrier
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//--- relabel, SL_Mode and TP_Mode DEFINE THE TRAINING LABELS, so they are in the weights-filename
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//--- fingerprint and changing either one re-keys the model and starts a fresh retrain. A user needs to
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//--- be able to see which pair the shipped model was actually trained on.
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enum STOP_LOSS_MODE
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{
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SL_INTELLIGENT = -1, // Intelligent (AI-confidence scaled)
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SL_ATR_x1 = 1, // ATR * 1 from entry
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SL_ATR_x2 = 2, // ATR * 2 from entry
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SL_ATR_x3 = 3, // ATR * 3 from entry
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};
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//--- Take-profit sizing mode. The ATR_* presets set the TP a fixed multiple of ATR FROM THE ENTRY
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//--- PRICE (no longer derived from the reward:risk ratio - that ratio was a pure
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//--- rejection filter). TP_INTELLIGENT scales the target UP with confidence (lets high-conviction
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//--- winners run further). Negative sentinel as above.
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//--- TP_PREV_SWING REMOVED 2026-07-31 alongside the swing-anchored stops: targeting the opposite swing
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//--- caps the reward at whatever structure happens to be overhead, which on a trending signal exits
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//--- well before the move is done and, paired with a swing-anchored stop, made the realised
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//--- reward:risk a property of the chart's geometry rather than of the setup.
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enum TAKE_PROFIT_MODE
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{
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TP_INTELLIGENT = -1, // Intelligent (AI-confidence scaled)
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TP_ATR_x1 = 1, // ATR * 1 from entry
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TP_ATR_x2 = 2, // ATR * 2 from entry
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TP_ATR_x3 = 3, // ATR * 3 from entry
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TP_ATR_x4 = 4, // ATR * 4 from entry
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TP_ATR_x6 = 6, // ATR * 6 from entry
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TP_ATR_x8 = 8, // ATR * 8 from entry
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TP_ATR_x10 = 10, // ATR * 10 from entry
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};
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//--- RISK_REWARD_RATIO removed 2026-08-09 along with its only consumer, the Min_Risk_Reward_Ratio
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//--- input. Deleted rather than left dangling: a live enum with no input behind it is exactly the shape
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//--- of the 2026-07 incident where a saved .set kept feeding a deleted option's ordinal back in and
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//--- trained ~250 eras on the wrong target (MT5 does not validate saved enum inputs). See
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//--- Variables\Inputs.mqh for why the ratio itself had to go.
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enum MONEY_RISK_PERCENT_PRESET
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{
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RISK_PCT_1 = 1, // 1
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RISK_PCT_2 = 2, // 2
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RISK_PCT_3 = 3, // 3
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RISK_PCT_4 = 4, // 4
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RISK_PCT_5 = 5, // 5
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};
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enum BARS_EXPIRATION
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{
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BARS_X1 = 1, // 1 Candle
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BARS_X2 = 2, // 2 Candles
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BARS_X3 = 3, // 3 Candles
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BARS_X5 = 5, // 5 Candles
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BARS_X10 = 10, // 10 Candles
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BARS_X20 = 20, // 20 Candles
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};
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//--- Entry order placement. All ATR offsets are measured from the CURRENT price (bid/ask), NOT the
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//--- swing - this is the deliberate change for stability. Sign picks the side, magnitude is the ATR
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//--- multiple:
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//--- MARKET - fill immediately at market.
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//--- LIMIT_*xATR - pending LIMIT that many ATR on the favorable side of bid/ask (buy below /
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//--- sell above): wait for a pullback into a better price.
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//--- STOP_*xATR - pending STOP that many ATR on the breakout side of bid/ask (buy above /
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//--- sell below): enter on continuation.
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//--- ENTRY_PREV_SWING - pending order anchored at the recent swing (buy at the lookback swing low /
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//--- sell at the swing high) - the one swing-anchored option kept as a choice.
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//--- ENTRY_INTELLIGENT - AI-confidence-scaled LIMIT pullback from bid/ask: a deep pullback when
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//--- confidence is low, collapsing to a market fill as confidence -> 1 (grab
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//--- high-conviction setups, demand a better price on marginal ones).
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//--- Non-MARKET results that clear the broker's stop-level distance become a pending order that
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//--- auto-expires after Signal_Expiration bars; anything closer just fills at market
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//--- (CExpertTrade::Buy/Sell handle the market-vs-limit-vs-stop routing off this price natively).
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enum ENTRY_MULTIPLIER
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{
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ENTRY_INTELLIGENT = -100, // Intelligent (AI-confidence scaled limit pullback)
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//ENTRY_PREV_SWING = -101, // Pending at previous swing low (buy) / swing high (sell)
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LIMIT_3xATR = -3, // Limit 3x ATR from bid/ask
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LIMIT_2xATR = -2, // Limit 2x ATR from bid/ask
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LIMIT_1xATR = -1, // Limit 1x ATR from bid/ask
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MARKET = 0, // Market order
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STOP_1xATR = 1, // Stop 1x ATR from bid/ask
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STOP_2xATR = 2, // Stop 2x ATR from bid/ask
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STOP_3xATR = 3, // Stop 3x ATR from bid/ask
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};
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enum TRAILING_STRATEGY
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{
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TRAILING_STRATEGY_NONE, // No Trailing Stop Strategy
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TRAILING_STRATEGY_ATR_x1, // ATR * 1 Trailing Strategy
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TRAILING_STRATEGY_ATR_x2, // ATR * 2 Trailing Strategy
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TRAILING_STRATEGY_ATR_x3, // ATR * 3 Trailing Strategy
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//--- Confidence-adaptive ATR trail: widens toward TRAIL_ATR_MAX_MULT when live AI confidence still
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//--- backs the position (lets winners run), tightens toward TRAIL_ATR_MIN_MULT as that confidence
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//--- weakens or flips against it (locks profit). See Trailing\TrailingIntelligent.mqh.
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TRAILING_STRATEGY_INTELLIGENT, // Intelligent (AI-confidence adaptive ATR) Trailing Strategy
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};
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enum MONEY_MANAGEMENT_STRATEGY
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{
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FIXED_RISK, // Fixed risk Percent of Account
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INTELLIGENT, // Intelligent lot size
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FIXED_LOT, // Fixed lot size
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};
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enum CLOSE_HOUR_OF_DAY
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{
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CLOSE_HOUR_DISABLED = -1, // Disabled
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CH_0 = 0, // 00Hxx
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CH_1 = 1, // 1Hxx
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CH_2 = 2, // 2Hxx
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CH_3 = 3, // 3Hxx
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CH_4 = 4, // 4Hxx
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CH_5 = 5, // 5Hxx
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CH_6 = 6, // 6Hxx
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CH_7 = 7, // 7Hxx
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CH_8 = 8, // 8Hxx
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CH_9 = 9, // 9Hxx
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CH_10 = 10, // 10Hxx
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CH_11 = 11, // 11Hxx
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CH_12 = 12, // 12Hxx
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CH_13 = 13, // 13Hxx
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CH_14 = 14, // 14Hxx
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CH_15 = 15, // 15Hxx
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CH_16 = 16, // 16Hxx
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CH_17 = 17, // 17Hxx
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CH_18 = 18, // 18Hxx
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CH_19 = 19, // 19Hxx
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CH_20 = 20, // 20Hxx
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CH_21 = 21, // 21Hxx
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CH_22 = 22, // 22Hxx
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CH_23 = 23, // 23Hxx
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};
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enum CLOSE_MINUTE_OF_HOUR
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{
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CLOSE_MINUTE_DISABLED = -1,// Disabled
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CM_0 = 0, // xxH00
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CM_5 = 5, // xxH05
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CM_10 = 10, // xxH10
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CM_15 = 15, // xxH15
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CM_20 = 20, // xxH20
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CM_25 = 25, // xxH25
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CM_30 = 30, // xxH30
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CM_35 = 35, // xxH35
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CM_40 = 40, // xxH40
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CM_45 = 45, // xxH45
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CM_50 = 50, // xxH50
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CM_55 = 55, // xxH55
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CM_60 = 60, // xxH60
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};
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enum CLOSE_DAY_OF_WEEK
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{
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CLOSE_DAY_DISABLED = -1, // Disabled
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CLOSE_MONDAY = 1, // Monday
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CLOSE_TUESDAY = 2, // Tuesday
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CLOSE_WEDNESDAY = 3, // Wednesday
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CLOSE_THURSDAY = 4, // Thursday
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CLOSE_FRIDAY = 5, // Friday
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CLOSE_EVERYDAY, // Every Day
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};
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enum NF_LOOKBACK_PRESETS
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{
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NF_DISABLED = -1, // Disabled
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M5 = 5, // 5 Minutes
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M15 = 15, // 15 Minutes
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M30 = 30, // 30 Minutes
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M45 = 45, // 45 Minutes
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M60 = 60, // 1 Hour
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M120 = 120, // 2 Hours
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M240 = 240, // 4 Hours
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};
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enum NF_IMPACT_PRESETS
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{
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HOLIDAYS = 0, //Holidays
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LOW = 1, // Low Impact News
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MEDIUM = 2, // Medium Impact News
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HIGH = 3, // High Impact News
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};
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enum TRADING_DIRECTION
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{
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BOTH, // Allow both long and short trades
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LONG_ONLY, // Allow only long (buy) trades
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SHORT_ONLY // Allow only short (sell) trades
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};
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enum PERCENTAGE_PRESETS
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{
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PCT_10 = 10, // 10%
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PCT_20 = 20, // 20%
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PCT_30 = 30, // 30%
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PCT_40 = 40, // 40%
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PCT_50 = 50, // 50%
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PCT_60 = 60, // 60%
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PCT_70 = 70, // 70%
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PCT_80 = 80, // 80%
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PCT_90 = 90, // 90%
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PCT_100 = 100, // 100%
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};
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//--- Min_Vote_Close's own scale. Separate from PERCENTAGE_PRESETS above purely so the Disabled entry is
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//--- offered ONLY where it means something - it would be nonsense on Min_Vote_Open or MinRecall, which
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//--- share that enum.
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//--- DISABLED is 101 rather than a flag or a negative sentinel because 101 is unreachable on BOTH scales
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//--- this one input drives, with no special-case branch anywhere:
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//--- - the rule-based path compares it against an AVERAGE of pattern weights, which cannot exceed 100
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//--- (CExpertSignalCustom::CheckClosePosition -> m_threshold_close);
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//--- - the AI early-exit path compares Min_Vote_Close/100.0 = 1.01 against a softmax confidence
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//--- magnitude, which cannot exceed 1.0 (same function, m_ai_exit_threshold).
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//--- So selecting Disabled switches off vote-driven closing entirely - positions then leave only via
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//--- stop-loss, take-profit, trailing, or the scheduled close-all - and it does so by arithmetic rather
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//--- than by an extra boolean anyone has to keep in sync.
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enum VOTE_CLOSE_PRESETS
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{
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VOTE_CLOSE_10 = 10, // 10%
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VOTE_CLOSE_20 = 20, // 20%
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VOTE_CLOSE_30 = 30, // 30%
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VOTE_CLOSE_40 = 40, // 40%
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VOTE_CLOSE_50 = 50, // 50%
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VOTE_CLOSE_60 = 60, // 60%
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VOTE_CLOSE_70 = 70, // 70%
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VOTE_CLOSE_80 = 80, // 80%
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VOTE_CLOSE_90 = 90, // 90%
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VOTE_CLOSE_100 = 100, // 100%
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VOTE_CLOSE_DISABLED = 101, // Disabled (exit only via SL/TP/trailing)
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};
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//--- Strength (tau) of the post-hoc logit adjustment / prior correction applied to the AI's 3-class
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//--- decision at inference (see AdjustedSignalFromSoftmax in ExpertSignalAIBase.mqh). The network is
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//--- trained on class-balance-oversampled data, so its raw softmax over-calls the rare Buy/Sell classes;
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//--- re-weighting each class by its measured true base rate (prior^tau) pulls the decision back toward the
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//--- real distribution. 0 = Off (raw argmax, may over-call), 100 = full Bayesian calibration to the true
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//--- base rate. Stored as a percent; divided by 100 to get tau.
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enum LOGIT_PRIOR_STRENGTH_PRESETS
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{
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LOGIT_PRIOR_OFF = 0, // Off (raw argmax - may over-call Buy/Sell)
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LOGIT_PRIOR_25 = 25, // 25% (light correction)
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LOGIT_PRIOR_50 = 50, // 50% (moderate)
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LOGIT_PRIOR_75 = 75, // 75% (strong)
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LOGIT_PRIOR_100 = 100, // 100% (full calibration to true base rate)
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};
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//--- FIRST_LAYER_NEURONS removed 2026-07-29. The first dense layer dominates the parameter count -
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//--- it is (inputWidth+1) x width - so its only defensible value is a function of the input width and
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//--- the amount of in-sample data, neither of which the user can see when picking from a dropdown. It
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//--- is now derived: see CExpertSignalAIBase::ComputeFirstLayerWidth().
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//--- Architecture-aware dense-topology presets are now folded directly into AI_CHOICE so the UI shows
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//--- one coherent selector instead of separate AI and topology choices. The dense taper that follows each
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//--- architecture-specific front-end is chosen by the selected preset itself.
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//--- LSTM's own recurrent hidden-unit count - previously silently piggybacked on HiddenLayersCount
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//--- (an unrelated dense-taper-depth setting), which meant it could never be tuned independently and
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//--- defaulted to a value (4) nobody actually chose on purpose. Decoupled into its own input.
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enum LSTM_HIDDEN_SIZE_PRESET
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|
{
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LSTM_HIDDEN_8 = 8, // 8 Units
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LSTM_HIDDEN_16 = 16, // 16 Units
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LSTM_HIDDEN_32 = 32, // 32 Units
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LSTM_HIDDEN_64 = 64, // 64 Units
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LSTM_HIDDEN_128 = 128, // 128 Units
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|
};
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//--- CONV's own output-filter count for its convolutional layer - previously silently piggybacked on
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//--- HiddenLayersCount too (same bug class as LstmHiddenSize above), defaulting to a bottleneck of 4
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|
//--- filters/bar. Decoupled into its own input.
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|
enum CONV_FILTER_COUNT_PRESET
|
|
{
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|
CONV_FILTERS_8 = 8, // 8 Filters
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|
CONV_FILTERS_16 = 16, // 16 Filters
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|
CONV_FILTERS_32 = 32, // 32 Filters
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|
CONV_FILTERS_64 = 64, // 64 Filters
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|
CONV_FILTERS_128 = 128, // 128 Filters
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|
};
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|
//--- Shared pooling shape for the Conv front-end used by both CONV and HYBRID. Keeping this
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|
//--- separate from ConvFilterCount lets the filter-bank width and the downsampling span be tuned
|
|
//--- independently, instead of smuggling one into the other.
|
|
//--- CONV_POOL_WINDOW_PRESET / CONV_POOL_STEP_PRESET removed 2026-07-29 along with the pooling
|
|
//--- stage itself - their "N Bars" labels described time-axis pooling the implementation could
|
|
//--- never perform. See AddConvStage() in Expert\ExpertSignalAIBase.mqh.
|
|
|
|
enum MIN_NEURONS_COUNT
|
|
{
|
|
MIN_NEURONS_10 = 10, // Min. 10 Neurons per layer
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|
MIN_NEURONS_20 = 20, // Min. 20 Neurons per layer
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|
MIN_NEURONS_30 = 30, // Min. 30 Neurons per layer
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|
MIN_NEURONS_40 = 40, // Min. 40 Neurons per layer
|
|
MIN_NEURONS_50 = 50, // Min. 50 Neurons per layer
|
|
};
|
|
// Value IS the reduction percentage applied per hidden layer (retention = 100-value), consumed
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|
// via BuildFreshTopology()'s n = n*((100-value)*0.01) taper - e.g. RF_70 keeps 30% of the previous
|
|
// layer's neurons, i.e. a genuine 70% reduction per layer, matching the label at face value.
|
|
enum NEURONS_REDUCTION_FACTOR
|
|
{
|
|
RF_10 = 10, // 10 % Neurons Reduction Per Layer
|
|
RF_20 = 20, // 20 % Neurons Reduction Per Layer
|
|
RF_30 = 30, // 30 % Neurons Reduction Per Layer
|
|
RF_40 = 40, // 40 % Neurons Reduction Per Layer
|
|
RF_50 = 50, // 50 % Neurons Reduction Per Layer
|
|
RF_60 = 60, // 60 % Neurons Reduction Per Layer
|
|
RF_70 = 70, // 70 % Neurons Reduction Per Layer
|
|
RF_80 = 80, // 80 % Neurons Reduction Per Layer
|
|
RF_90 = 90, // 90 % Neurons Reduction Per Layer
|
|
};
|
|
enum OUTPUT_NEURONS_COUNT
|
|
{
|
|
OUTPUT_REGRESSION = 1, // Regression Algorithm
|
|
OUTPUT_CLASSIFICATION = 3, // Classification Algorithm
|
|
};
|
|
//--- 2026-07-30: the dense-DEPTH suffix is gone from every entry. Depth is now derived alongside the
|
|
//--- width and the taper it has to be consistent with (ComputeHiddenLayerCount) - asking a user to pick
|
|
//--- "3 layers" while the code derives the width those layers taper between is asking them to make half
|
|
//--- a decision with no way to see the other half. This selector now chooses only the thing that is
|
|
//--- genuinely a modelling CHOICE: which front-end reads the input sequence.
|
|
enum AI_CHOICE
|
|
{
|
|
AI_NONE = 0, // Disabled (classic signals only)
|
|
AI_MLP = 1, // MLP (dense only)
|
|
AI_CONV = 2, // CONV (convolutional front-end)
|
|
AI_LSTM = 3, // LSTM (recurrent front-end)
|
|
AI_HYBRID = 4, // HYBRID (convolutional + recurrent)
|
|
AI_META = 5, // META (trade-quality head over classic candidates - trains, no votes yet)
|
|
};
|
|
// Confidence used to scale SL/TP, gate early AI exits, and (Intelligent MM) scale lot size.
|
|
// AI confidence comes from the signal filter's live prediction (0..1); DB confidence comes
|
|
// from the historical time-based win rate of the currently traded patterns (0..1). Blended
|
|
// averages both, so a pattern is only sized up when both the model and its track record agree.
|
|
enum CONFIDENCE_SOURCE
|
|
{
|
|
CONF_AI = 0, // AI signal confidence only
|
|
CONF_DB = 1, // Database win-rate confidence only
|
|
CONF_BLENDED = 2, // Average of AI and database confidence
|
|
};
|
|
// How many bars to wait, after a candidate ZigZag reversal bar, before trusting the real ADZigZag
|
|
// indicator's verdict on it as a training label - see CExpertSignalAIBase's m_swingConfirmationBars
|
|
// declaration comment. A ZigZag's most recent 1-3 legs can still repaint as new bars arrive, so this
|
|
// must be generous enough to let a leg fully settle (bumped from the old fractal-based system's
|
|
// default of 20 to 100 for exactly that reason). A value of 0 is clamped up to a 1-bar minimum
|
|
// internally, never used to mean "no delay".
|
|
enum SWING_CONFIRMATION_PRESET
|
|
{
|
|
SC_10 = 10, // 10 Bars
|
|
SC_20 = 20, // 20 Bars
|
|
SC_30 = 30, // 30 Bars
|
|
SC_50 = 50, // 50 Bars
|
|
SC_100 = 100, // 100 Bars
|
|
SC_200 = 200, // 200 Bars
|
|
};
|
|
enum MAX_ERAS_PRESET
|
|
{
|
|
ME_100 = 100, // 100 Eras
|
|
ME_200 = 200, // 200 Eras
|
|
ME_300 = 300, // 300 Eras
|
|
ME_500 = 500, // 500 Eras
|
|
ME_1000 = 1000, // 1000 Eras
|
|
};
|
|
//--- percentage of the study period held back as out-of-sample data never trained on;
|
|
//--- value is the OOS share, in-sample share is the remainder (e.g. OOS_30 -> 70% IS / 30% OOS)
|
|
enum OOS_SPLIT_PRESET
|
|
{
|
|
OOS_10 = 10, // 90% IS / 10% OOS
|
|
OOS_20 = 20, // 80% IS / 20% OOS
|
|
OOS_30 = 30, // 70% IS / 30% OOS
|
|
OOS_40 = 40, // 60% IS / 40% OOS
|
|
OOS_50 = 50, // 50% IS / 50% OOS
|
|
};
|
|
//--- RISK_LIMIT_PCT_PRESET REMOVED 2026-08-02. It backed MaxDailyLossPct/MaxDrawdownPct as a dropdown
|
|
//--- of eight fixed percentages, which no funded-account programme is obliged to match - 4.5% or 3.75%
|
|
//--- were unreachable. Both inputs are now free-entry doubles (Variables\Inputs.mqh) validated at init.
|
|
//--- Note for anyone reinstating an enum input here: MT5 does NOT validate a saved enum value against
|
|
//--- the current enum, so a .set file holding a deleted member loads as a silent out-of-range int - the
|
|
//--- failure mode that trained four topologies on the wrong barrier (project memory: stale enum wrong
|
|
//--- target). Changing these two to doubles removes that exposure rather than renaming it.
|
|
//+------------------------------------------------------------------+
|