Diagnosing an Index Error in Stock Ranking Training

Summary

This document records a failure in a stock-ranking training module. The run loads 6,711 training rows, begins data and feature preparation, then stops with an IndexError while calculating maximum discounted cumulative gain. The traceback points to code that uses each training label as an index into a label-count array, suggesting a mismatch between label values and the range the ranking routine expects.

The log does not provide the label column’s contents, the module’s expected relevance levels, or a confirmed fix. It therefore serves as a troubleshooting clue rather than a complete diagnosis. A practitioner investigating a similar failure could inspect the target labels, verify that they are valid nonnegative relevance categories within the configured range, and check how examples are grouped into ranking queries. The record gives no evidence that changing model settings or feature names alone resolves the problem, and the underlying cause remains unverified.

Key ideas

• The training run fails during ranking metric preparation, before model training completes.
• The traceback identifies label indexing in the maximum DCG calculation as the immediate failure point.
• The log suggests checking that relevance labels fall within the range expected by the ranker.
• The document does not show the label data or establish a confirmed root cause or remedy.

Tags

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