Generators#

Dataset generators produce synthetic datasets of a user-specified shape, dimensionality, and cardinality. Synthetic data is useful for a number of tasks including experimenting with data of various shapes, augmenting an already existing dataset with more data, or for testing and demonstration purposes.

Generate a Dataset#

To generate a Dataset object with n rows:

public generate(int $n) : Dataset

Example

use Rubix\ML\Datasets\Generators\Blob;

$generator = new Blob([0, 0], 1.0);

$dataset = $generator->generate(3);

var_dump($dataset);

Output

object(Rubix\ML\Datasets\Unlabeled) {
  ["samples":protected]=>
  array(3) {
    [0]=>
    array(2) {
      [0]=> float(-0.2729673885539)
      [1]=> float(0.43761840244204)
    }
    [1]=>
    array(2) {
      [0]=> float(-1.2718092282012)
      [1]=> float(-1.9558245484829)
    }
    [2]=>
    array(2) {
      [0]=> float(1.1774185431405)
      [1]=> float(0.05168623824664)
    }
  }
}

Dimensionality#

Return the dimensionality of the samples produced by the generator:

public dimensions() : int

Example

var_dump($generator->dimensions());

Output

int(2)