Adaptive Rate Limiting with Machine Learning Predictions

Architect an intelligent rate limiting system that uses machine learning to dynamically adjust API throttling based on historical usage patterns, current system load, and predictive demand forecasting. Develop a model that can automatically detect potential DDoS attempts, distinguish between legitimate traffic spikes and malicious activities, and dynamically adjust rate limit windows. Include a detailed implementation strategy for feature extraction, model training, and real-time inference.