View source: R/DatetimeTrendPlots.R
ComputeDatetimeTrendPlots | R Documentation |
Compute datetime trend plots for datetime partitioned model. This includes Accuracy over Time, Forecast vs Actual, and Anomaly over Time plots.
ComputeDatetimeTrendPlots(
model,
backtest = 0,
source = SourceType$Validation,
forecastDistanceStart = NULL,
forecastDistanceEnd = NULL
)
model |
An S3 object of class dataRobotModel like that returned by the function GetModel, or each element of the list returned by the function ListModels. |
backtest |
integer or character. Optional. Compute plots for a specific backtest.
Use the backtest index starting from zero.
To compute plots for holdout, use |
source |
character. Optional. The source of the data for the backtest/holdout.
Must be one of |
forecastDistanceStart |
integer. Optional. The start of forecast distance range (forecast window) to compute. If not specified, the first forecast distance for this project will be used. Only for time series supervised models. |
forecastDistanceEnd |
integer. Optional. The end of forecast distance range (forecast window) to compute. If not specified, the last forecast distance for this project will be used. Only for time series supervised models. |
Forecast distance specifies the number of time steps between the predicted point and the origin point.
For the multiseries models only first 1000 series in alphabetical order and an average plot for them will be computed.
Maximum 100 forecast distances can be requested for calculation in time series supervised projects.
An integer value that can be used as the jobId parameter in a subsequent call
to WaitForJobToComplete
.
## Not run:
projectId <- "59a5af20c80891534e3c2bde"
modelId <- "5996f820af07fc605e81ead4"
model <- GetModel(projectId, modelId)
jobId <- ComputeDatetimeTrendPlots(model)
WaitForJobToComplete(projectId, jobId) # optional step
## End(Not run)
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