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SPLK-5001 · Question #105

Outlier detection is an analysis method that groups together data points into high density clusters. Data points that fall outside of these high density clusters are considered to be what?

The correct answer is A. Anomalies. In outlier detection, points that lie outside the high‑density clusters - i.e., those not fitting into any cluster - are by definition anomalies, as they deviate significantly from the normal data

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Question

Outlier detection is an analysis method that groups together data points into high density clusters. Data points that fall outside of these high density clusters are considered to be what?

Options

  • AAnomalies
  • BBaselined
  • CNon-conformatives
  • DInconsistencies

How the community answered

(46 responses)
  • A
    91% (42)
  • B
    2% (1)
  • C
    2% (1)
  • D
    4% (2)

Explanation

In outlier detection, points that lie outside the high‑density clusters - i.e., those not fitting into any cluster - are by definition anomalies, as they deviate significantly from the normal data

Topics

#outlier detection#anomaly detection#clustering#behavioral analysis

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