`gemclus.data`.gstm¶

gemclus.data.gstm(n=500, alpha=2, df=1, random_state=None)[source]¶

Reproduces the Gaussian-Student Mixture dataset from the GEMINI article.

Parameters:

n: int, default=500: The number of samples to draw from the dataset.
alpha: float, default=2:: This parameter controls how close the means of the Gaussian distribution and the location of the Student-t distribution are.
df: float, default=1: The degrees of freedom for the Student-t distribution.
random_state: int, RandomState instance or None, default=None: Determines random number generation for dataset creation. Pass an int for reproducible output across multiple runs.

Returns:

X: ndarray of shape (n,2): The samples of the dataset in an array of shape n_samples x n_features
y: ndarray of shape (n,): The component of the GMM from which each sample was drawn.

References

GEMINI - Ohl, L., Mattei, P. A., Bouveyron, C., Harchaoui, W., Leclercq, M., Droit, A., & Precioso, F.: (2022, October). Generalised Mutual Information for Discriminative Clustering. In Advances in Neural Information Processing Systems.

Examples using `gemclus.data.gstm`¶