XGBoost Troubleshooting - Teradata Vantage

Machine Learning Engine Analytic Function Reference

Product
Teradata Vantage
Release Number
8.00
1.0
Published
May 2019
Language
English (United States)
Last Update
2019-11-22
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blj1506016597986.ditamap
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dita:id
B700-4003
lifecycle
previous
Product Category
Teradata Vantageā„¢

Problem: Function runs slowly or runs out of memory.

Workarounds:

  • Increase the value of NumBoostedTrees (the number of parallel boosted trees to consider during prediction).

    Each vworker processes each of its assigned tree-boosting operations sequentially. When you increase the value of NumBoostedTrees, each boosting operation operates on smaller subset of input data.

  • Decrease the input data footprint by minimizing the number of columns.
  • Decrease the size of a tree in memory by adjusting the values of these arguments:
    • MinNodeSize
    • MaxDepth
    • ColumnSubSampling