Advanced ensemble ML system combining XGBoost, LightGBM, Random Forest, Neural Networks & TensorFlow with real-time WebSocket data and self-learning AI for accurate predictions.
We combine multiple state-of-the-art ML algorithms for the most accurate predictions
Multiple models vote together for final prediction. Weighted voting system where stronger models get more influence based on cross-validation scores.
Multi-branch TensorFlow architecture with BatchNorm, Dropout, and L2 regularization. Trained with early stopping and adaptive learning rates.
Dynamic pattern recognition with confidence-weighted learning rates. Adapts to market changes with anti-pattern detection and weight decay.
WebSocket connection for live game data. Instant feature extraction and prediction within milliseconds of new round data.
55+ engineered features including sequence encoding, momentum indicators, volatility, entropy, seasonal patterns, and transition probabilities.
Logistic Regression meta-model learns to combine predictions from all base models. Cross-validation ensures no overfitting.
From data collection to prediction in 4 simple steps
Real-time WebSocket streams live game data. Historical API fetches past results for training.
55+ features extracted: sequences, streaks, volatility, momentum, entropy & patterns.
6 models analyze features. Ensemble voting with weighted confidence produces final prediction.
AI learns from results. Patterns updated with dynamic rates. Models retrained every 4 hours.
6 specialized models working together in ensemble
Join now and get access to our AI-powered Dragon Tiger prediction system