azuremlsdk: log_predictions_to_run – R documentation

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log_predictions_to_run

Log a predictions metric to a run

Description

log_predictions_to_run() logs a metric score that can be used to compare the distributions of true target values to the distribution of predicted values for a regression task.

The predictions are binned and standard deviations are calculated for error bars on a line chart.

Usage

log_predictions_to_run(name, value, description = "", run = NULL)

Arguments

`name`	A string of the name of the metric.
`value`	A named list containing name, version, and data properties.
`description`	(Optional) A string of the metric description.
`run`	The `Run` object. If not specified, will default to the current run from the service context.

Value

None

Examples

data <- list("bin_averages" = c(0.25, 0.75),
             "bin_errors" = c(0.013, 0.042),
             "bin_counts" = c(56, 34),
             "bin_edges" = c(0.0, 0.5, 1.0))
predictions <- list("schema_type" = "predictions",
                    "schema_version" = "v1",
                    "data" = data)
log_predictions_to_run("mypredictions", predictions)

azuremlsdk

Interface to the 'Azure Machine Learning' 'SDK'

v1.10.0

MIT + file LICENSE

Authors

Diondra Peck [cre, aut], Minna Xiao [aut], AzureML R SDK Team [ctb], Microsoft [cph, fnd], Google Inc. [cph] (Examples and Tutorials), The TensorFlow Authors [cph] (Examples and Tutorials), RStudio Inc. [cph] (Examples and Tutorials)

Initial release