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weight_col: <table.column> (Optional)

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Description

weight_col specifies the target-table column used to generate a canonical WEIGHT column in the training table. This enables native weighted training directly from training table generation, without requiring a custom weighted training table override.
  • weight_col must be in strict table.column form.
  • weight_col must reference a column on the inferred target table.
  • The referenced column must be numerical (int, float, or decimal).
  • Expressions are not supported (for example: SUM(...), AVG(...), MAX(...), COUNT(*)).
  • When set, training table generation produces a canonical WEIGHT column.
  • Rows with null WEIGHT are dropped before final stats/materialization.
  • For link prediction (non-array targets), if multiple rows map to one (ENTITY, TARGET[, time bucket]), WEIGHT is aggregated with MAX by default.
  • For LIST_DISTINCT array-target link prediction, weights are aggregated per (ENTITY, TARGET) and emitted as a list aligned with TARGET.
  • For temporal link prediction, weight aggregation is bucket-local and uses the same time bucketing as label construction.
  • For binary classification, if both weight_col and majority_sampling_ratio are set, both are applied according to weight_mode.

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Supported Task Types

  • All static queries
  • Temporal link prediction
Not supported for temporal node prediction and forecasting.

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Example

weight_col: <table.column>
weight_col: TRANSACTIONS.AMOUNT
weight_col: ORDERS.ORDER_VALUE

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Default Values

run_modeDefault Value
FASTNone
NORMALNone
BESTNone