Beyond accuracy: Stabilizing feature importance in GWRF/RF for soil heavy metal mapping

Yoshiyasu Takefuji1

  • 1Faculty of Data Science, Musashino University, 3-3-3 Ariake Koto-ku, Tokyo, 135-8181, Japan.

Summary

Qin et al. (2025) mapped soil heavy metals using geographically weighted random forest (GWRF) and random forest (RF), improving accuracy. They identified key predictors but noted limitations in feature importance validation, recommending rank-stability auditing for robust interpretation.

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