ML Brain — Learning & Memory

Watch the model learn from every trade in real time
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Training Examples
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Rolling Accuracy
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Mode
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Normalizer Samples
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Classifier Bias
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Last Trained

Learning Curve

Cumulative Accuracy
Win
Loss

Cumulative PnL (SOL)

Exit Reason Breakdown

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Feature Memory — What the Brain Has Learned

Each feature has a learned weight. Positive (green) = bullish signal. Negative (red) = bearish signal. The normalizer tracks the running mean and standard deviation of each feature across all training samples.

Feature Direction Classifier Weight Visual Regressor Weight Mean Std Dev
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Recent Training Examples

Time Token Result Peak PnL (SOL) Exit Reason
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