RequestCrossSeriesDetection: Format a cross series with group by columns.
In datarobot: 'DataRobot' Predictive Modeling API

RequestCrossSeriesDetection

R Documentation

Format a cross series with group by columns.

Description

Call this function to request the project be formatted as a cross series project with a group by column.

Usage

RequestCrossSeriesDetection(
  project,
  dateColumn,
  multiseriesIdColumns = NULL,
  crossSeriesGroupByColumns = NULL,
  maxWait = 600
)

Arguments

`project`	character. Either (1) a character string giving the unique alphanumeric identifier for the project, or (2) a list containing the element projectId with this identifier.
`dateColumn`	character. The name of the column containing the date that defines the time series.
`multiseriesIdColumns`	character. Optional. The Series ID to demarcate the series. If not specified, DataRobot will attempt to automatically infer the series ID.
`crossSeriesGroupByColumns`	character. Optional. Column to split a cross series into further groups. For example, if every series is sales of an individual product, the cross series group could be e product category with values like "men's clothing", "sports equipment", etc. Requires multiseries with `useCrossSeries` enabled.
`maxWait`	integer. The maximum time (in seconds) to wait for the model job to complete.

Details

Note that this function no longer needs to be called directly, but is called indirectly as a part of SetTarget (which itself is called indirectly as part of StartProject) when you pass a crossSeriesGroupByColumn using CreateDatetimePartitionSpecification.

Value

A named list which contains:

timeSeriesEligible logical. Whether or not the series is eligible to be used for time series.
crossSeriesEligible logical. Whether or not the cross series group by column is eligible for cross-series modeling. Will be NULL if no cross series group by column is used.
crossSeriesEligibilityReason character. The type of cross series eligibility (or ineligibility).
timeUnit character. For time series eligible features, the time unit covered by a single time step, e.g. "HOUR", or NULL for features that are not time series eligible.
timeStep integer. Expected difference in time units between rows in the data. Will be NULL for features that are not time series eligible.