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LEDDrift

LED stream generator with concept drift.

This class is an extension of the LED generator whose purpose is to add concept drift to the stream.

Parameters

  • seed (int) – defaults to None

    If int, seed is used to seed the random number generator; If RandomState instance, seed is the random number generator; If None, the random number generator is the RandomState instance used by np.random.

  • noise_percentage (float) – defaults to 0.0

    The probability that noise will happen in the generation. At each new sample generated, a random number is generated, and if it is equal or less than the noise_percentage, the led value will be switched

  • irrelevant_features (bool) – defaults to False

    Adds 17 non-relevant attributes to the stream.

  • n_drift_features (int) – defaults to 0

    The number of attributes that have drift.

Attributes

  • desc

    Return the description from the docstring.

Examples

>>> from river import synth

>>> dataset = synth.LEDDrift(seed = 112, noise_percentage = 0.28,
...                          irrelevant_features= True, n_drift_features=4)

>>> for x, y in dataset.take(5):
...     print(list(x.values()), y)
[1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 1] 8
[0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1] 5
[1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 1, 0, 1] 8
[0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 1, 1, 0] 3
[0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0] 5

Methods

take

Iterate over the k samples.

Parameters

  • k (int)

Notes

An instance is generated based on the parameters passed. If has_noise is set then the total number of attributes will be 24, otherwise there will be 7 attributes.