- datetimePartitionColumn
character. The name of the column whose values as dates
are used to assign a row to a particular partition
- autopilotDataSelectionMethod
character. Optional. Whether models created
by the autopilot should use "rowCount" or "duration" as their dataSelectionMethod
- validationDuration
character. Optional. The default validationDuration for the
backtests
- holdoutStartDate
character. The start date of holdout scoring data
(RFC 3339 format). If holdoutStartDate is specified, holdoutDuration must also be specified.
- holdoutDuration
character. Optional. The duration of the holdout scoring data.
If holdoutDuration is specified, holdoutStartDate must also be specified.
- disableHoldout
logical. Optional. Whether to suppress allocating the holdout fold.
If set to TRUE, holdoutStartDate and holdoutDuration must not be specified.
- gapDuration
character. Optional. The duration of the gap between training and
holdout scoring data.
- numberOfBacktests
integer. The number of backtests to use.
- backtests
list. List of BacktestSpecification the exact specification of backtests to use.
The indexes of the specified backtests should range from 0 to numberOfBacktests - 1.
If any backtest is left unspecified, a default configuration will be chosen.
- useTimeSeries
logical. Whether to create a time series project (if TRUE) or an OTV
project which uses datetime partitioning (if FALSE). The default behavior is to create an
OTV project.
- defaultToKnownInAdvance
logical. Whether to default to treating features as known in
advance. Defaults to FALSE. Only used for time series project. Known in advance features are
expected to be known for dates in the future when making predictions (e.g., "is this a
holiday").
- featureDerivationWindowStart
integer. Optional. Offset into the past to define how far
back relative to the forecast point the feature derivation window should start. Only used for
time series projects. Expressed in terms of the timeUnit of the
datetimePartitionColumn.
- featureDerivationWindowEnd
integer. Optional. Offset into the past to define how far
back relative to the forecast point the feature derivation window should end. Only used for
time series projects. Expressed in terms of the timeUnit of the
datetimePartitionColumn.
- featureSettings
list. Optional. A list specifying settings for each feature. For each
feature you would like to set feature settings for, pass the following in a list:
featureName character. The name of the feature to set feature settings.
knownInAdvance logical. Optional. Whether or not the feature is known in advance.
Used for time series only. Defaults to FALSE.
doNotDerive logical. Optional. If TRUE, no time series derived features
(e.g., lags) will be automatically engineered from this feature. Used for time series only.
Defaults to FALSE.
- treatAsExponential
character. Optional. Defaults to "auto". Used to specify whether to
treat data as exponential trend and apply transformations like log-transform. Use values
from TreatAsExponential enum.
- differencingMethod
character. Optional. Defaults to "auto". Used to specify differencing
method to apply if data is stationary. Use values from DifferencingMethod.
- windowsBasisUnit
character. Optional. Indicates which unit is the basis for the feature
derivation window and forecast window. Valid options are a time unit (see TimeUnit)
or "ROW".
- periodicities
list. Optional. A list of periodicities for different times. Must be
specified as a list of lists, where each list item specifies the `timeSteps` for a
particular `timeUnit`. Should be "ROW" if windowsBasisUnit is "ROW".
- forecastWindowStart
integer. Optional. Offset into the future to define how far forward
relative to the forecast point the forecast window should start. Only used for time series
projects. Expressed in terms of the timeUnit of the datetimePartitionColumn.
- forecastWindowEnd
integer. Optional. Offset into the future to define how far forward
relative to the forecast point the forecast window should end. Only used for time series
projects. Expressed in terms of the timeUnit of the datetimePartitionColumn.
- multiseriesIdColumns
list. A list of the names of multiseries id columns to define series
- useCrossSeries
logical. If TRUE, cross series features will be included. For
details, see "Calculating features across series" in the time series section of the
DataRobot user guide.
- aggregationType
character. Optional. The aggregation type to apply when creating cross
series features. Must be either "total" or "average". See SeriesAggregationType.
- 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.
- calendar
character. Optional. Either the calendar object or calendar id to use
for this project.