Predict
Retrieve model predictions
This function can be used to predict with a particular model.
Usage
Predict(model, predictionDataset, classPrefix = "class_",
maxWait = 600, forecastPoint = NULL, predictionsStartDate = NULL,
predictionsEndDate = NULL, type = "response",
includePredictionIntervals = FALSE, predictionIntervalsSize = NULL)Arguments
- 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.
- predictionDataset
object. Either a dataframe of data to predict on or a DataRobot prediction dataset object of class
dataRobotPredictionDataset.- classPrefix
character. For multiclass projects returning prediction probabilities, this prefix is prepended to each class in the header of the dataframe. Defaults to "class_".
- maxWait
integer. The maximum time (in seconds) to wait for the prediction job to complete.
- forecastPoint
character. Optional. The point relative to which predictions will be generated, based on the forecast window of the project. Only specified in time series projects.
- predictionsStartDate
datetime. Optional. Only specified in time series projects. The start date for bulk predictions. This parameter should be provided in conjunction
predictionsEndDate. Can't be provided withforecastPointparameter.- predictionsEndDate
datetime. Optional. Only specified in time series projects. The end date for bulk predictions. This parameter should be provided in conjunction
predictionsStartDate. Can't be provided withforecastPointparameter.- type
character. String specifying the type of response for binary classifiers; see Details.
- includePredictionIntervals
logical. Optional. Should prediction intervals bounds should be part of predictions? Only available for time series projects. See "Details" for more info.
- predictionIntervalsSize
numeric. Optional. Size of the prediction intervals, in percent. Only available for time series projects. See "Details" for more info.
Details
The contents of the return vector depends on the modeling task - binary classification, multiclass classification, or regression; whether or not the underlying data is time series, multiseries, cross-series, or not time series; and the value of the /codetype parameter. For non-time-series regression tasks, the type parameter is ignored and a vector of numerical predictions of the response variable is returned.
This function will error if the requested job has errored, or
if it does not complete within maxWait seconds.
See RequestPredictions and GetPredictions for more details.
Value
Vector of predictions, depending on the modeling task ("Binary", "Multiclass", or "Regression") and the value of the type parameter; see Details.
Examples
# NOT RUN {
trainIndex <- sample(nrow(iris) * 0.7)
trainIris <- iris[trainIndex, ]
testIris <- iris[-trainIndex, ]
project <- StartProject(trainIris, "iris", target = "Petal_Width", wait = TRUE)
model <- GetRecommendedModel(project)
predictions <- Predict(model, testIris)
# Or, if prediction intervals are desired (datetime only)
model <- GetRecommendedModel(datetimeProject)
predictions <- Predict(datetimeModel,
dataset,
includePredictionIntervals = TRUE,
predictionIntervalsSize = 100,
type = "raw")
# }