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Data Anomaly Detection

bookChallenge: Using DBSCAN Clustering to Detect Outliers

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Now, you will apply the DBSCAN clustering algorithm to detect outliers on a simple Iris dataset.
You have to:

  1. Specify the parameters of the DBScan algorithm: set eps equal to 0.35 and min_samples equal to 6.
  2. Fit the algorithm and provide clustering.
  3. Get outlier indexes and indexes of normal data. Pay attention that outliers detected by the algorithm have a -1 label.

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Sektion 3. Kapitel 2
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bookChallenge: Using DBSCAN Clustering to Detect Outliers

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Opgave

Swipe to start coding

Now, you will apply the DBSCAN clustering algorithm to detect outliers on a simple Iris dataset.
You have to:

  1. Specify the parameters of the DBScan algorithm: set eps equal to 0.35 and min_samples equal to 6.
  2. Fit the algorithm and provide clustering.
  3. Get outlier indexes and indexes of normal data. Pay attention that outliers detected by the algorithm have a -1 label.

Løsning

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Var alt klart?

Hvordan kan vi forbedre det?

Tak for dine kommentarer!

close

Awesome!

Completion rate improved to 6.67
Sektion 3. Kapitel 2
single

single

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