Introducing classification analysis in SAP Analytics Cloud Smart Predict

After completing this lesson, you will be able to:

After completing this lesson, you will be able to:

  • Explain classification analysis in Smart Predict

Use cases for classification models

Using augmented analytics to identify potential employee churn

In the interaction below, we will walk you through a case study for using classification models to identify churn.

What sorts of topics can we investigate with a classification model?

  • Categorize credit card transactions as genuine or fraudulent
  • Classify bank loan applications as either safe or risky
  • Determine whether a prospect will respond or not to a marketing campaign
  • Identify employees who are likely to resign
  • Identify customers at risk of terminating their mobile contracts to change provider (churn)
  • Classify if an email is spam or not
  • Determine of a machine is likely to break down in the next 60 minute interval, or not

Classification analysis in Smart Predict

Classification analysis identifies the category a new observation belongs to, on the basis of a training set of data containing observations whose category membership is known.

If you have data of employees who leave a role, then you could build a classification model that will predict the probability of other employees resigning.

For a classification model in SAP Analytics Cloud Smart Predict, the target variable must be binary nominal, which means the target can be recorded as 1 or 0 to signify yes or no.

Three different classification analysis visualizations

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