summary.outlieroutputs

Pretty-prints outliers as output by the `predict` function from an Outlier Tree
model (as generated by function `outlier.tree`), or by `extract.training.outliers`.
Same as function `print` (see the documentation of `print` for more information about
the parameters).

Outlier detection method that flags suspicious values within observations,
constrasting them against the normal values in a user-readable format, potentially
describing conditions within the data that make a given outlier more rare.
Full procedure is described in Cortes (2020) <doi:10.48550/arXiv.2001.00636>.
Loosely based on the 'GritBot' <https://www.rulequest.com/gritbot-info.html> software.

David Cortes

outliertree

Explainable Outlier Detection Through Decision Tree Conditioning

summary.outlieroutputs function

<dl><dt>object</dt>
<dd>Outliers as returned by predict method on an object from `outlier.tree`.</dd>
<dt>outliers_print</dt>
<dd>Maximum number of outliers to print.</dd>
<dt>...</dt>
<dd>Not used.</dd></dl>

Arguments

Print outliers in human-readable format — summary.outlieroutputs

<dl>

<dt>object</dt>
<dd>Outliers as returned by predict method on an object from `outlier.tree`.</dd>


<dt>outliers_print</dt>
<dd>Maximum number of outliers to print.</dd>


<dt>...</dt>
<dd>Not used.</dd>

</dl>

summary.outlieroutputs: Print outliers in human-readable format

Description

Usage

Value

Arguments

See Also