quant-ml-purged-cv-integration

What problem does it solve?

This Skill prevents data leakage during the training of Machine Learning models on financial time-series data by implementing Purged Cross-Validation (CV).

Core Features & Use Cases

• Data Leakage Prevention: Ensures that training data never overlaps with validation data in time.
• Financial Time-Series Focus: Specifically designed for sequential financial data where temporal order is critical.
• Use Case: When training a stock price prediction model, this Skill ensures that the data used for validation in any given fold has not been seen during the training of that fold, preventing unrealistic performance metrics.

Quick Start

Integrate the CombinatorialPurgedKFold class into your ML model's training pipeline to perform purges before validation splits.