API Reference / datasets / generators / clustering /

moons.py

Moons generator: two interleaving half circles.

Produces a pair of crescents that curve into one another, with Gaussian jitter. Like circles it is not linearly separable, but the clusters are elongated rather than nested.

Classes

Moons

class datasets.generators.clustering.moons.Moons(ClusteringGenerator)

Two Moons data generator.

Generates two interleaving half circles (moons). This is a classic non-linearly separable dataset.
Constructor 
__init__(
    self,
    n_samples: int = 100,
    noise: float = 0.1,
    shuffle: bool = True,
    random_state: Optional[int] = None,
)

Parameters

n_samples
int = 100
Number of samples to generate.
noise
float = 0.1
Standard deviation of Gaussian noise.
shuffle
bool = True
Whether to shuffle the samples.
random_state
int or None = None
Random seed for reproducibility.
python 
>>> from tuiml.datasets.generators.clustering import Moons
>>> gen = Moons(n_samples=1000, noise=0.1, random_state=0)
>>> data = gen.generate()
>>> data.X.shape
(1000, 2)
>>> sorted(set(data.y.tolist()))
[0, 1]

Methods

generate (self) -> GeneratedData

Generate two moons data.

Returns
GeneratedData
Generated dataset with feature array X of shape (n_samples, 2) and moon labels y (0 or 1).
get_parameter_schema (cls) -> Dict[str, Any]

Return JSON Schema for constructor parameters.