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What is ML Trade Classification Hierarchy about?

This document outlines the expanded decision hierarchy of an ML model used to classify trades into probability buckets (0-8) based on various market indicators. Key layers include volatility regime, momentum shape, RSI stability, relative strength context, volume pressure, and micro-pattern features, each influencing the trade classification process. The hierarchy emphasizes that successful trades require a combination of favorable conditions across these layers to reach higher probability buckets.

Author

Aman Rathore

Language

EN