4eae763849
The plateau/regression line printed balancedOosEra as the current value while comparing against m_bestBalancedOos, which has held the SELECTION score sincea142749. Two different metrics in one sentence, so HYBRID logged "regressed from best 14.4% to 34.0%" a hundred times - a regression to a higher number, which is not a thing. The comparison itself was right (selectionScore, coverage weighted, genuinely below best); only the print was wrong.1039ad9relabelled these strings but missed that this site passes the wrong variable. The startup config line had the same shape of gap: it printed the dense taper and called itself self-verifying while the DERIVED conv and recurrent stages - the ones that dominate CONV/LSTM/HYBRID - were invisible. It now shows the width into and out of each front-end stage, and flags the case where the dense stack is wider than the vector reaching it (a linear fan-out cannot recover what the bottleneck discarded; it only adds parameters). Flagged, not silently reshaped - that would re-key trained topologies mid-comparison. UsesConvStage()/UsesLstmStage() replace HasConvBeforeLstm() as the primitive, so each subclass declares its composition once and both the capacity budget and the config line derive from it rather than restating it. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
63 行
无行尾
3.6 KiB
MQL5
63 行
无行尾
3.6 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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virtual bool InitIndicators(CIndicators *indicators) override;
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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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SetIdentity("Hybrid", "HYB");
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}
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//+------------------------------------------------------------------+
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//| Create indicators and bootstrap/load the network. |
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//+------------------------------------------------------------------+
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bool CSignalHYBRID::InitIndicators(CIndicators *indicators)
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{
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return InitNeuralNetwork(indicators);
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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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//+------------------------------------------------------------------+ |