The intuition and maths for the H-stat used to find interactions in machine learning models
Towards Data Science 6:38 pm on May 28, 2024
The H-statistic (H-stat) is an analytical tool used in machine learning to identify interaction terms that could significantly improve model performance. Developed by Friedman, it quantifies the importance of interactions between features on predictive accuracy.
- Identifying Interaction Terms: The H-statistic uncovers significant interaction effects.
- Analytical Tool for Machine Learning Models: It serves as a method to assess feature interactions.
- Developed by Friedman (1979): The H-stat was introduced in academic literature.
- Predictive Accuracy Enhancement: It measures the impact on model performance when interactions are considered.
- Applicability in Various Models: The H-stat can be applied across different machine learning algorithms.
https://towardsdatascience.com/understanding-freidmans-h-statistic-h-stat-for-interactions-43fb5e31a586
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