Fig 14.opju: SHAP Analysis of a Random Forest Model for Load Prediction

An Origin project file containing the SHAP value analysis for a Random Forest model. The file presents feature contributions of input variables to predictions of displacement and ultimate load, along with feature importance comparisons. It was authored by Hongtao Zhang and last updated on June 1, 2026.

Use Cases

• Analyzing feature contributions to model predictions based on SHAP values.
• Comparing the relative importance of input features for displacement and load predictions.
• Understanding the decision-making process of a Random Forest model for structural or mechanical applications.

Strengths

• The dataset is focused on model interpretability, providing SHAP values and feature importance comparisons.
• It is shared under a permissive CC-BY-4.0 license, allowing for reuse with attribution.

Limitations

• The dataset is very small at 33.3 KB, indicating limited scope.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

figshare

Freshness

Last updated 2026-06-01 17:33:05; freshness should be verified.