The integration of Machine Learning stands as a prominent ... This is the most interpretable ML algorithm with the highest XAI performance. However, it suffers from low prediction accuracy. Ensemble ...

However, existing molecular captioning approaches often underutilize diverse molecular modalities and lack interpretability ... a novel explainable molecular captioning framework that integrates ...

In a new study, University of Illinois Urbana-Champaign researchers use a new AI-driven approach that combines machine learning with an interpretability ... but their accuracy can vary significantly.

However, existing molecular captioning approaches often underutilize diverse molecular modalities and lack interpretability ... Accuracy;Training;Data models;Data ...

Abstract: This paper presents a comprehensive framework for integrating Explainable Artificial Intelligence ... multi-context agricultural dataset and a novel interpretability-accuracy metric to ...

Can machine learning be both accurate and explainable ... this by integrating explainable artificial intelligence (XAI) techniques into a powerful stacking ensemble model. The authors combined three ...

Explainable AI (XAI) has emerged to address ... Support Vector Machines, Random Forests, Multilayer Perceptron, and Extreme Gradient Boosting, evaluating predictive accuracy and interpretability.

Chongwei Chen, DataNumen, Inc. One effective strategy for improving transparency in black-box AI systems is using explainable AI (XAI ... embedding model interpretability from the start provides ...