Adaptive Rate Limiting with Machine Learning Predictive Models

Develop an intelligent rate-limiting middleware for PHP APIs that uses machine learning algorithms to dynamically adjust throttling based on historical usage patterns. Create a system that can distinguish between legitimate traffic spikes and potential abuse, with adaptive threshold calculations that consider user behavior, time of day, and request characteristics. Implement a comprehensive logging and visualization dashboard to track rate limit decisions and machine learning model performance.