In Anomaly Detection using K-means, outliers are calculated on the basis of the following process:
Get the distance between each point and its nearest centroid. The biggest distances are considered as anomaly.
So we don't take the top 10% data points for anomaly detection but take the points farthest away from their nearest centroids and consider them as anomalies.
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