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cs.LG2025
Unveiling Location-Specific Price Drivers: A Two-Stage Cluster Analysis for Interpretable House Price Predictions
Paul Gümmer, Julian Rosenberger, Mathias Kraus +2
House price valuation remains challenging due to localized market variations. Existing approaches often rely on black-box machine learning models, which lack interpretability, or s…
cs.LG2024
Challenging the Performance-Interpretability Trade-off: An Evaluation of Interpretable Machine Learning Models
Sven Kruschel, Nico Hambauer, Sven Weinzierl +3
Machine learning is permeating every conceivable domain to promote data-driven decision support. The focus is often on advanced black-box models due to their assumed performance ad…
cs.LG2024
IGANN Sparse: Bridging Sparsity and Interpretability with Non-linear Insight
Theodor Stoecker, Nico Hambauer, Patrick Zschech +1
Feature selection is a critical component in predictive analytics that significantly affects the prediction accuracy and interpretability of models. Intrinsic methods for feature s…