log_predictions_to_run

A string of the name of the metric.

name

A named list containing name, version, and data properties.

value

(Optional) A string of the metric description.

description

The <code>Run</code> object. If not specified, will default
to the current run from the service context.

<code>log_predictions_to_run()</code> 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.

Interface to the 'Azure Machine Learning' Software Development Kit
('SDK'). Data scientists can use the 'SDK' to train, deploy, automate, and
manage machine learning models on the 'Azure Machine Learning' service. To
learn more about 'Azure Machine Learning' visit the website:
<https://docs.microsoft.com/en-us/azure/machine-learning/service/overview-what-is-azure-ml>.

Diondra Peck

azuremlsdk

Interface to the 'Azure Machine Learning' 'SDK'

Minna Xiao

AzureML R SDK Team 

Microsoft 

 Google Inc.

 The TensorFlow Authors

 RStudio Inc.

log_predictions_to_run function

<pre>data &lt;- 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 &lt;- list("schema_type" = "predictions",
 "schema_version" = "v1",
 "data" = data)
log_predictions_to_run("mypredictions", predictions)
</pre>

log_predictions_to_run: Log a predictions metric to a run

Description

Usage

Arguments

Value

Examples