 ramseshk
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b0fab62a87
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feat: add 10 new ML models for auction optimization (Phases 1-6)
Phase 1 - Quick Wins:
- QuantileEnsemble: P10/P50/P90 predictions for risk-aware bidding
- MinutesSurvivalModel: Weibull AFT for minutes distribution modeling
Phase 2 - Adaptive Auction:
- BanditAuctionSolver: Thompson Sampling for live auction bids
- OpponentBidModel: Predict competitor bids via LightGBM
- BudgetOptimizer: Bayesian optimization for role-level allocation
Phase 3 - Deep Learning:
- RLAuctionPolicy: Double DQN agent for auction strategy
- SetTransformer: Team composition valuation via set-based ML
Phase 4 - Probabilistic:
- BayesianPlayerModel: Hierarchical pooling for rookie uncertainty
- ConformalPredictor: Calibrated prediction intervals
Phase 5 - Chemistry & Form:
- PlayerChemistryGAT: Graph attention network for player synergies
- PlayerFormModel: Hawkes process for form momentum
Phase 6 - Causal:
- TransferCausalModel: Causal forest for transfer effects
- AuctionEffectAnalyzer: Bid adjustment from causal analysis
81 tests passing
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2026-08-11 17:56:03 +08:00 |
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