Z Scale Standardizer#
A method of centering and scaling a dataset such that it has 0 mean and unit variance, also known as a Z-Score. Although Z-Scores are technically unbounded, in practice they mostly fall between -3 and 3 - that is, they are no more than 3 standard deviations away from the mean.
Data Type Compatibility: Continuous
|1||center||true||bool||Should we center the sample dataset?|
Return the means calculated by fitting the training set:
public means() : array
Return the variances calculated during fitting:
public variances() : array
Return the standard deviations calculated during fitting:
public stddevs() : array
use Rubix\ML\Transformers\ZScaleStandardizer; $transformer = new ZScaleStandardizer(true);
- T. F. Chan et al. (1979). Updating Formulae and a Pairwise Algorithm for Computing Sample Variances.