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How to Score a Dataset Using Predict Only

Since we’ve already covered how to score a dataset using Construct, it’s only fair that we show you how to score using the Predict Scoring program. We’ll start at the point where you save your scoring model within Predict. After memorizing your model in the Model tab, you’ll want to move down to the Compare Models tab. This tab allows you to compare any two models side-by-side. Once you’ve decided which model you like better, you’re ready to save it by selecting the model and clicking the “Save Scoring Model” as button, as shown below.

Predict will prompt you to navigate to where you’d like the file to be saved, and will save it with a .rism (Rapid Insight Scoring Model) extension. After saving the .rism file, you’ll want to open the Predict Scoring Module by going to your Start Menu and navigating to Rapid Insight Inc. -> Predict -> Scoring, as shown below.

Once inside the scoring module, you’ll need to click the “Select Dataset” button and navigate to where the dataset you’d like to score is located on your machine. After loading in your dataset, you’ll see all of the variables within it populate the ‘Dataset Variables’ window. Next, you’ll need to click the “Select Scoring Model” button and navigate to where the scoring model (.rism) file you’d like to use is located. Once you find the model, its equation will show up in the corresponding window.

Before you start the scoring process, you have a couple of options detailing how you’d like the model to be scored. The first option, shown above in the green box, allows you to validate the model by looking at the decile analysis resulting from the scoring process. The second option, shown in the blue box, allows you to output the scores as well as the corresponding deciles or percentiles. After you’ve selected the appropriate options, click on the “Start Scoring” button, decide where you’d like your scores to output, and Predict will score your dataset in the way that you request.

-Caitlin Garrett, Statistical Analyst at Rapid Insight

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