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);
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());
int(2)