Deep learning for NeuroImaging in Python.

Note

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surfify.datasets._samples_generator.make_classification(ico_vertices, n_samples=40, n_classes=2, scale=1, seed=None)[source]¶

Generate a random n-class classification problem.

Parameters:

ico_vertices : array (N, 3)

the icosahedron’s vertices.

n_samples : int, default 40

the number of gene rate samples.

n_classes : int, default 2

the number of classes.

scale : int or list of int, default 1

the scale of each Gaussian.

seed : int, default None

seed to control random number generation.

Returns:

X : ndarray (n_samples, n_classes, n_vertices)

the generated samples.

y : ndarray (n_vertices, )

the assocaited labels.