Overview
SHAP values help explain the influence of individual features (data inputs, such as geological data, historical drilling results, or geophysical anomalies) on the AI model’s predictions. By showing how much each feature contributed to the prediction outcome, SHAP values offer insights into the importance and impact of each feature in the system’s decision-making process.
SHAP Value Graph
The SHAP value graph ranks features by how much they influenced the model’s predictions:
Higher SHAP values: These features had a significant impact on the model’s predictions and appear higher and further to the right on the graph.
Lower SHAP values: These features had a smaller impact and are displayed lower on the graph.
Color Scale: Indicates the magnitude of SHAP values.
The graph helps you quickly see which features the model prioritized when making predictions.
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