This node detects and treats the outliers for each of the selected columns individually by means of interquartile range (IQR).
To detect the outliers for a given column, the first and
third
quartile (Q_{1}, Q_{3}) is computed.
An observation is flagged an outlier if it lies
outside the range
R = [Q_{1} - k(IQR), Q_{3} + k(IQR)] with
IQR = Q_{3} - Q_{1} and k >= 0.
Setting k = 1.5 the smallest value in R corresponds,
typically, to the lower end of a boxplot's whisker and largest value
to its upper end.
Providing grouping information allows to detect outliers only
within their respective groups.
If an observation is flagged an outlier, one can either replace it by some other value or remove/retain the corresponding row.
Missing values contained in the data will be ignored, i.e., they will neither be used for the outlier computation nor will they be flagged as an outlier.
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To use this node in KNIME, install the extension KNIME Statistics Nodes from the below update site following our NodePit Product and Node Installation Guide:
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