Skip to content


Linear Discriminant Analysis#

Linear Discriminant Analysis (LDA) is a supervised dimensionality reduction technique that selects the most informative features using information in the class labels. More formally, LDA finds a linear combination of features that characterizes or best discriminates two or more classes.

Interfaces: Transformer, Stateful, Persistable

Data Type Compatibility: Continuous only


# Name Default Type Description
1 dimensions int The target number of dimensions to project onto.


use Rubix\ML\Transformers\LinearDiscriminantAnalysis;

$transformer = new LinearDiscriminantAnalysis(20);

Additional Methods#

Return the proportion of information lost due to the transformation:

public lossiness() : ?float