Robust Z Score#
A statistical anomaly detector that uses modified Z scores that are robust to preexisting outliers. The modified Z score uses the median and median absolute deviation (MAD) unlike the mean and standard deviation of a standard Z score which are sensitive to outliers. Anomalies are flagged if their final weighted Z score exceeds the user-defined threshold.
Note: An alpha value of 1 means the estimator only considers the maximum absolute z score whereas a setting of 0 indicates that only the average z score factors into the final score.
Data Type Compatibility: Continuous
|1||threshold||3.5||float||The minimum Z score to be flagged as an anomaly.|
|2||alpha||0.5||float||The weight of the maximum per sample z score in the overall anomaly score.|
Return the median of each feature column in the training set:
public medians() : ?array
Return the median absolute deviation (MAD) of each feature column in the training set:
public mads() : ?array
use Rubix\ML\AnomalyDetection\RobustZScore; $estimator = new RobustZScore(3.0, 0.3);
- B. Iglewicz et al. (1993). How to Detect and Handle Outliers.