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A proprietary normalized indicator (0-100) combining advanced machine learning analysis with technical indicators, momentum, and risk metrics.
Our engine trains 5 ML models on historical patterns (no raw data redistributed) and transforms predictions into:
100% Compliant: No raw market data is redistributed. All outputs are proprietary analytical transformations.
Ensemble methods combine multiple ML models (weighted by R² accuracy) to produce more reliable predictions than any single model.
Instead of showing raw price predictions, we calculate a normalized score (0-100) representing market sentiment and direction strength.
Backtesting validates model performance by testing predictions against historical outcomes (direction accuracy, not price accuracy to maintain compliance).
Shows how similarly different models predict directional changes. High correlation = strong consensus.
A single metric (0-100%) indicating overall model agreement.