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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

Parameters#

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

Example#

use Rubix\ML\Transformers\LinearDiscriminantAnalysis;

$transformer = new LinearDiscriminantAnalysis(20);

Additional Methods#

Return the proportion of information lost due to the transformation:

public lossiness() : ?float


Last update: 2021-03-06