On the interpretability of the SVM model for predicting infant mortality in Bangladesh

On the interpretability of the SVM model for predicting infant mortality in Bangladesh

Abstract Background Although machine learning (ML) models are well-liked for their outperformance in prediction, greatly avoided due to the lack of intuition and explanation of their predictions. Interpretable ML is, therefore, an emerging research field that combines the performance and interpretab...

Full description

Saved in:
Bibliographic Details
Main Authors: Md Abu Sayeed, Azizur Rahman, Atikur Rahman, Rumana Rois
Format: Article
Language:English
Published: BMC 2024-10-01
Series:Journal of Health, Population and Nutrition
Subjects:
Individual conditional expectation
Interpretable machine learning models
Global surrogate models
Global interpretability techniques
Local interpretability techniques
Sigmoid kernel
Online Access:https://doi.org/10.1186/s41043-024-00646-9
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1186/s41043-024-00646-9

Similar Items