most citedBeyond explaining: XAI-based Adaptive Learning with SHAP Clustering for Energy Consumption Prediction

2 citations · 3 across the 2 of their papers we have counts for

collaborators

2 papers

cs.DB2024★ 1 cited

Open-Source Drift Detection Tools in Action: Insights from Two Use Cases

Rieke Müller, Mohamed Abdelaal, Davor Stjelja

Data drifts pose a critical challenge in the lifecycle of machine learning (ML) models, affecting their performance and reliability. In response to this challenge, we present a mic…

cs.LG2024★ 2 cited

Beyond explaining: XAI-based Adaptive Learning with SHAP Clustering for Energy Consumption Prediction

Tobias Clement, Hung Truong Thanh Nguyen, Nils Kemmerzell +2

This paper presents an approach integrating explainable artificial intelligence (XAI) techniques with adaptive learning to enhance energy consumption prediction models, with a focu…