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docs/en/stack/ml/df-analytics/dfa-outlierdetection.asciidoc
@@ -12,6 +12,13 @@ training data set to teach {oldetection} to recognize outliers. Unsupervised
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{oldetection} uses various machine learning techniques to find which data points
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are unusual compared to the majority of the data points.
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+You can create {oldetection} {dfanalytics-jobs} in {kib} or by using the
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+{ref}/put-dfanalytics.html[create {dfanalytics-jobs} API].
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+
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+[discrete]
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+[[dfa-outlier-algorithms]]
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+=== {oldetection-cap} algorithms
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In the {stack}, we use an ensemble of four different distance and density based
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{oldetection} methods. By default, you don't need to select the methods or
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provide any parameters, but you can override the default behavior if you like.
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