[source] # 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](#z-scale-standardizer). $$ {\displaystyle z^\prime = {x - \operatorname {median}(X) \over MAD }} $$ **Interfaces:** [Transformer](api.md#transformer), [Stateful](api.md#stateful), [Reversible](api.md#reversible), [Persistable](../persistable.md) **Data Type Compatibility:** Continuous ## Parameters | # | Name | Default | Type | Description | |---|---|---|---|---| | 1 | center | true | bool | Should we center the data at 0? | ## Example ```php use Rubix\ML\Transformers\RobustStandardizer; $transformer = new RobustStandardizer(true); ``` ## Additional Methods Return the medians calculated by fitting the training set: ```php public medians() : array ``` Return the median absolute deviations calculated during fitting: ```php public mads() : array ```