8.4 Scoring and Consumption of Insights
Now that we’ve experimented with our recommendations model and have determined the optimal run, we can move on to scoring the model to generate product recommendations.
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8.4.1 - Score a Model based on a Recipe
After training a model, we can use the model to score and as such, have the model build recommendations which can be activated through targeting.
To start scoring, let's re-open Training Run 1 by clicking it.
After opening Training Run 1, you'll see a full overview of the Training Run, and in the future, more visualization options will be added.
To score, you have to click the + Score button in the top right corner of your screen.
In the next step, you again have to select an Input Dataset. Let's choose the AEP Demo - Recommendations Input .
After selecting the Input Dataset, click Next .
In the next step, you need to select a dataset to which Platform will output results. In this case, select the AEP Demo - Recommendations Output .
After selecting the Output Dataset, click Next .
In the next screen, you'll see the Model's Configuration parameters.
After updating the Model's Configuration parameters, click Finish .
A Scoring Run is now created, and has a status of Pending .
And 1-2 minutes later, the Scoring Run's status will change to Complete .
And finally, let's preview the results. Click on Scoring Run 1
Next, click the Preview Scoring Results Dataset .
Next Step: Summary and benefits