forked from animatedread/Warrior_EA
8c0186c850
Every AI signal repeated the same five-line InitIndicators override that did nothing but call InitNeuralNetwork. The cause was an access mismatch, not a design: CExpertSignalCustom declares InitIndicators public, the AI base redeclared it PROTECTED, and each subclass had to redeclare it public to be reachable by CExpert. Worse, the base's own override does a different job entirely - it creates the OHLC/ZigZag feature indicators - and InitNeuralNetwork called it back scope-qualified to stop the virtual dispatch landing in the subclass. Two jobs, one virtual name, and a recursion trap held off by a scope qualifier. The feature-indicator step is now InitFeatureIndicators() (protected, non-virtual, named for what it does) and the AI base carries the single public InitIndicators override. CONV/HYBRID/LSTM/PAI/META drop their copies and are now purely identity plus topology, which is the classic signal file's shape. Comment pass on ExpertSignalAIBase.mqh, -100 lines with every constant and every measured number kept. Three claims in the tier block were stale and inverted - it named CalibratedConfidenceMagnitude() as the tiering input where the code deliberately uses the RAW magnitude, and it described the signal DB as re-ranking each tier when ApplyPatternWeight declines the DB from the end of era 1. Also dropped a paragraph whose subject was a previous version of the comment, and moved two notes down onto the constants they document (CONV_COMPRESSION_DIVISOR was 16 lines and three unrelated defines away from its own text). Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
59 lines
No EOL
3.5 KiB
MQL5
59 lines
No EOL
3.5 KiB
MQL5
//+------------------------------------------------------------------+
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//| Warrior_EA |
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//| AnimateDread |
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//| |
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//+------------------------------------------------------------------+
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#include "..\Expert\ExpertSignalAIBase.mqh"
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// wizard description start
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//+------------------------------------------------------------------+
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//| Description of the class |
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//| Title=Signals of indicator 'CNN-LSTM AI' |
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//| Type=SignalAdvanced |
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//| Name=CNN-LSTM AI |
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//| ShortName=HYB |
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//| Class=CSignalHYBRID |
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//| Page=signal_hybrid |
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//+------------------------------------------------------------------+
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// wizard description end
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//+------------------------------------------------------------------+
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//| Class CSignalHYBRID. |
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//| Purpose: a single fused CNN-LSTM signal that stacks Conv+Pool |
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//| layers before the LSTM layer, then the shared dense taper. |
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//| The base AI voting path still applies, so this module trades as |
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//| one coherent signal instead of three loosely synchronized ones. |
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//+------------------------------------------------------------------+
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class CSignalHYBRID : public CExpertSignalAIBase
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{
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protected:
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virtual bool AddCustomLayers(CArrayObj *topology) override;
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//--- AddCustomLayers below appends BOTH stages, conv first - so this topology's LSTM is fed the conv
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//--- feature map rather than the raw input. Keep these in step with AddCustomLayers: they are what let
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//--- the capacity budget size the recurrent block against its REAL fan-in (see LstmFanIn()).
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virtual bool UsesConvStage(void) const override { return true; }
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virtual bool UsesLstmStage(void) const override { return true; }
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virtual ENUM_ACTIVATION HiddenLayerActivation(void) override { return TANH; }
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public:
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CSignalHYBRID(void);
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};
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//+------------------------------------------------------------------+
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//| Constructor |
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//+------------------------------------------------------------------+
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CSignalHYBRID::CSignalHYBRID(void)
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{
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//--- Display name follows the 2026-08-15 rename (AI_CONVLSTM: conv front-end + LSTM).
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//--- The SHORT id stays "HYB" deliberately: it names the model folder
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//--- (Neural Networks\State\HYB\) and changing it would orphan every model trained
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//--- under the old path - a rename is not worth a forced retrain.
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SetIdentity("ConvLSTM", "HYB");
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}
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//+------------------------------------------------------------------+
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//| Conv + Pool front-end followed by an LSTM sequence layer. This |
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//| matches the standalone CONV front-end exactly, then adds LSTM. |
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//+------------------------------------------------------------------+
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bool CSignalHYBRID::AddCustomLayers(CArrayObj *topology)
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{
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//--- "the standalone CONV front-end exactly, then adds LSTM" is now enforced by construction:
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//--- both stages are the same code CSignalCONV and CSignalLSTM run.
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return AddConvStage(topology) && AddLstmStage(topology);
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}
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//+------------------------------------------------------------------+ |