Unlabeled datasets are used to train unsupervised learners and for feeding unknown samples into an estimator to make predictions during inference. As their name implies, they do not require a corresponding label for each sample.


# Param Default Type Description
1 samples array A 2-dimensional array consisting of rows of samples and columns with feature values.
2 validate true bool Should we validate the input?

Additional Methods#

Factory Methods#

Build a new unlabeled dataset with validation:

public static build(array $samples = []) : self

Build a new unlabeled dataset foregoing validation:

public static quick(array $samples = []) : self


use Rubix\ML\Datasets\Unlabeled;

$samples = [
    [0.1, 20, 'furry'],
    [2.0, -5, 'rough'],
    [0.001, -10, 'rough'],

$dataset = new Unlabeled($samples); // With validation

$dataset = new Unlabeled($samples, false); // Without validation

$dataset = Unlabeled::build($samples);  // With validation

$dataset = Unlabeled::quick($samples);  // Without validation