Preparing Predictive Scenario Output Datasets

Objectives

After completing this lesson, you will be able to:

Visualizing Output Data Generated by a Classification or Regression Predictive Scenario

There are three ways to create visualizations using output data generated from a classification or regression predictive scenario.

To create R visualizations using your output dataset in a story, you must ensure that the following is kept in the dataset:

The application data set variables, if these variables are not available from another source
The predictions
The key variable(s)

You can then upload the output data set directly in a story.

Once you check that the relevant information is in the dataset, you can create your story. This creates an embedded model in a story.

It's also possible to add new data to a previously created prediction. To do this, you must keep the following information in your output dataset:

Using the key variable, or variables, you can blend the predictions with other data sources in a story.

You can create a model using the output dataset to create a story. From the story, you can create your R visualization.

There are three ways to create visualizations using output data generated from a time series predictive scenario:

Once you check that the relevant information is in the dataset, you can create your story. This creates an embedded model in a story.

To combine existing data with your predictions, you need the forecasts in your output data set
The date and signal are selected automatically
Using the date variable, you can blend the predictions with other data sources, in the context of a story

You can first use the output data set to create a model and then consume it in a story.