Introducing Classification Analysis in SAP Analytics Cloud Smart Predict

Objectives
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 case study, we walk you through a scenario 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 responds to a marketing campaign or not.
  • Identify employees who are likely to resign.
  • Identify customers who are at risk of canceling their mobile contracts to change provider (churn).
  • Classify if an e-mail is spam or not.
  • Determine if 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 that 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 predicts the probability of other employees resigning.

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

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