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Fixing LightGBM Feature Name Errors in BigQuant

Article BigQuant
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Summary

This brief BigQuant support exchange explains a feature-name mismatch that prevents a LightGBM module from locating an input column. The module is given a calculated expression as the feature name, while the DataFrame column is actually named “ma.” The suggested fix is to add an input-feature-name module configured with that column name, allowing the model step to reference the existing feature correctly.

The exchange ends with the user confirming the issue was resolved. It documents a practical workflow error rather than a modeling method: calculated feature values and the names passed into a training module must align. It provides no details about the dataset, model settings, prediction quality, or whether the feature itself is suitable, so it should not be read as evidence about LightGBM performance.

Key ideas

  • The reported training problem comes from a mismatch between a feature expression and the DataFrame column name.
  • The LightGBM module expects the actual input column name, which is identified as “ma.”
  • The proposed remedy is to configure an input feature name module with the matching column name.
  • The user reports that this resolved the issue, but the exchange provides no information about model performance.

Tags

Machine learning

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.