Which of the following is false about train data and test data in Azure ml studio?

--- title: "Train and deploy your first model with Azure ML" author: "David Smith" date: "`r Sys.Date[]`" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{Train and deploy your first model with Azure ML} %\VignetteEngine{knitr::rmarkdown} \use_package{UTF-8} --- In this tutorial, you learn the foundational design patterns in Azure Machine Learning. You'll train and deploy a Generalized Linear Model to predict the likelihood of a fatality in an automobile accident. After completing this tutorial, you'll have the practical knowledge of the R SDK to scale up to developing more-complex experiments and workflows. In this tutorial, you learn the following tasks: * Connect your workspace * Load data and prepare for training * Upload data to the datastore so it is available for remote training * Create a compute resource * Train a caret model to predict probability of fatality * Deploy a prediction endpoint * Test the model from R ##Prerequisites If you don't have access to an Azure ML workspace, follow the [setup tutorial][//azure.github.io/azureml-sdk-for-r/articles/configuration.html] to configure and create a workspace. ##Set up your development environment The setup for your development work in this tutorial includes the following actions: * Install required packages * Connect to a workspace, so that your local computer can communicate with remote resources * Create an experiment to track your runs * Create a remote compute target to use for training To run this notebook in an Azure ML Compute Instance, visit the [Azure Machine Learning studio][//ml.azure.com] and browse to Notebooks > Samples > Azure ML gallery > Samples > R > > vignettes. Click the "..." icon next to vignettes and chose "clone". Launch RStudio Server from the link in the "Compute" tab. In RStudio, select "File > New Project > Existing Directory" and browse to the cloned "Vignettes" folder. ###Install required packages This tutorial assumes you already have the Azure ML SDK installed. [If you are running this vignette from an RStudio instance in an Azure ML Compute Instance, the package is already installed for you.] Go ahead and load the **azuremlsdk** package. ```{r eval=FALSE} library[azuremlsdk] ``` The training and scoring scripts [`accidents.R` and `accident_predict.R`] have some additional dependencies. If you plan on running those scripts locally, make sure you have those required packages as well. ###Load your workspace Instantiate a workspace object from your existing workspace. The following code will load the workspace details from the **config.json** file. You can also retrieve a workspace using [`get_workspace[]`][//azure.github.io/azureml-sdk-for-r/reference/get_workspace.html]. ```{r load_workpace, eval=FALSE} ws