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Robust Standardizer#

This standardizer transforms continuous features by centering them around the median and scaling by the median absolute deviation (MAD) referred to as a robust or modified Z-Score. The use of robust statistics make this standardizer more immune to outliers than Z Scale Standardizer.

\[ {\displaystyle z^\prime = {x - \operatorname {median}(X) \over MAD }} \]

Interfaces: Transformer, Stateful, Reversible, Persistable

Data Type Compatibility: Continuous

Parameters#

# Name Default Type Description
1 center true bool Should we center the data at 0?

Example#

use Rubix\ML\Transformers\RobustStandardizer;

$transformer = new RobustStandardizer(true);

Additional Methods#

Return the medians calculated by fitting the training set:

public medians() : array

Return the median absolute deviations calculated during fitting:

public mads() : array


Last update: 2021-07-03