Requires that this model belongs to a datetime partitioned project. If it does not, an error will occur when submitting the job
RequestFrozenDatetimeModel(
model,
trainingRowCount = NULL,
trainingDuration = NULL,
trainingStartDate = NULL,
trainingEndDate = NULL,
timeWindowSamplePct = NULL
)An integer value that can be used as the modelJobId parameter in subsequent calls to the GetDatetimeModelFromJobId function.
An S3 object of class dataRobotModel like that returned by the function GetModel, or each element of the list returned by the function ListModels.
integer. (optional) the number of rows of data that should be used to train the model.
character. string (optional) a duration string specifying what time range the data used to train the model should span.
character. string(optional) the start date of the data to train to model on (" be used.
character. string(optional) the end date of the data to train the model on (" will be used.
integer. (optional) May only be specified when the requested model is a time window (e.g. duration or start and end dates). An integer between 1 and 99 indicating the percentage to sample by within the window. The points kept are determined by a random uniform sample.
Frozen models use the same tuning parameters as their parent model instead of independently optimizing them to allow efficiently retraining models on larger amounts of the training data.
In addition to trainingRowCount and trainingDuration, frozen datetime models may be trained on an exact date range. Only one of trainingRowCount, trainingDuration, or trainingStartDate and trainingEndDate should be specified. Models specified using trainingStartDate and trainingEndDate are the only ones that can be trained into the holdout data (once the holdout is unlocked).
if (FALSE) {
projectId <- "59a5af20c80891534e3c2bde"
modelId <- "5996f820af07fc605e81ead4"
model <- GetDatetimeModel(modelId)
RequestFrozenDatetimeModel(model)
}
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