An Ensemble Framework for Explainable Geospatial Machine Learning Models

arXiv:2403.03328v1 Announce Type: new
Abstract: Analyzing spatial varying effect is pivotal in geographic analysis. Yet, accurately capturing and interpreting this variability is challenging due to the complexity and non-linearity of geospatial data. Herein, we introduce an integrated framework that merges local spatial weighting scheme, Explainable Artificial Intelligence (XAI), and cutting-edge machine learning technologies to bridge the gap between traditional geographic analysis models and general machine learning approaches. Through tests on synthetic datasets, this framework is verified to enhance the interpretability …

abstract analysis artificial artificial intelligence arxiv complexity cs.cy cs.lg data edge ensemble explainable artificial intelligence framework geospatial intelligence machine machine learning machine learning models pivotal spatial type xai