kumoai.pquery.TrainingTableGenerationPlan#
- class kumoai.pquery.TrainingTableGenerationPlan[source]#
Configuration parameters that define the construction of a Kumo training table from a predictive query. Please see the Kumo documentation for more information.
- Variables:
split – (
str
) A custom split that is used to generate a training, validation, and test set in the training table (default:"inferred"
). Supported Task Types: Alltrain_start_offset – (
int
|"inferred
”) Defines the numerical offset from the most recent entry to use to generate training data labels. Unless a custom time unit is specified in the aggregation, this value is in days (default:"inferred"
). Supported Task Types: Temporaltrain_end_offset – (
int
|"inferred"
) Defines the numerical offset from the most recent entry to not use to generate training data labels. Unless a custom time unit is specified in the aggregation, this value is in days (default:"inferred"
). Supported Task Types: Temporaltimeframe_step – (
int
|"inferred"
) Defines the step size of generating time intervals for training table generation (default:"inferred"
). Supported Task Types: Temporalforecast_length – (
int
) Turns a node regression problem into a forecasting problem (default:1
). Supported Task Types: Temporal Regressionlag_timesteps – (
int
) For forecasting problems, leverage the auto-regressive labels as inputs. This parameter controls the number of previous values that should be considered as auto-regressive labels (default:0
). Supported Task Types: Temporal Regressionyear_over_year – (
bool
) For forecasting problems, integrate Year-Over-Year features as inputs to give more attention to the data from the previous year when making a prediction. (default:False
)