skada.datasets.make_shifted_blobs

skada.datasets.make_shifted_blobs(n_samples=100, n_features=2, shift=0.1, noise=None, centers=None, cluster_std=1.0, random_state=None, return_X_y=True, return_dataset=False)

Generate source and shift target isotropic Gaussian blobs .

Parameters:

n_samplesint, default=100

It is the total number of points equally divided among clusters.

n_featuresint, default=2

The number of features for each sample.

shiftfloat or array like, default=0.10

If float, it is the value of the translation for every target feature. If array_like, each element of the sequence indicates the value of the translation for each target features.

noisefloat or array_like, default=None

If float, standard deviation of Gaussian noise added to the data. If array-like, each element of the sequence indicate standard deviation of Gaussian noise added to the source and target data.

centersint or ndarray of shape (n_centers, n_features), default=None

The number of centers to generate, or the fixed center locations. If n_samples is an int and centers is None, 3 centers are generated. If n_samples is array-like, centers must be either None or an array of length equal to the length of n_samples.

cluster_stdfloat or array-like of float, default=1.0

The standard deviation of the clusters.

shufflebool, default=True

Shuffle the samples.

random_stateint, RandomState instance or None, default=None

Determines random number generation for dataset creation. Pass an int for reproducible output across multiple function calls.

return_X_yboolean, optional (default=True)

Returns source and target dataset as a pair of (X, y) tuples (for the source and the target respectively). Otherwise returns tuple of (X, y, sample_domain) where sample_domain is a categorical label for the domain where sample is taken.

return_datasetboolean, optional (default=False)

When set to True, the function returns DomainAwareDataset object.

Returns:

(X, y, sample_domain)tuple if return_X_y=True

Tuple of (data, target, sample_domain), see the description below.

dataBunch

Dictionary-like object, with the following attributes.

X: ndarray

Samples from all sources and all targets given.

yndarray

Labels from all sources and all targets.

sample_domainndarray

The integer label for domain the sample was taken from. By convention, source domains have non-negative labels, and target domain label is always < 0.

domain_namesdict

The names of domains and associated domain labels.

datasetDomainAwareDataset

Dataset object.