RandomRBFGenerator#
- class capymoa.stream.generator.RandomRBFGenerator[source]#
Bases:
MOAStream
An Random RBF Generator
>>> from capymoa.stream.generator import RandomRBFGenerator ... >>> stream = RandomRBFGenerator() >>> stream.next_instance() LabeledInstance( Schema(generators.RandomRBFGenerator ), x=[0.21 1.01 0.092 0.272 0.45 0.226 0.212 0.373 0.583 0.297], y_index=1, y_label='class2' ) >>> stream.next_instance().x array([0.68807095, 0.62508298, 0.36161375, 0.29484898, 0.46067958, 0.83491016, 0.69794979, 0.75702471, 0.79436834, 0.7605141 ])
- __init__(
- model_random_seed: int = 1,
- instance_random_seed: int = 1,
- number_of_classes: int = 2,
- number_of_attributes: int = 10,
- number_of_centroids: int = 50,
Construct a Random RBF Generator .
- Parameters:
instance_random_seed – Seed for random generation of instances, defaults to 1
number_of_classes – The number of classes of the generated instances, defaults to 2
number_of_attributes – The number of attributes of the generated instances, defaults to 10
number_of_drifting_centroids – The number of drifting attributes, defaults to 2
- __iter__() Iterator[_AnyInstance] [source]#
Get an iterator over the stream.
This will NOT restart the stream if it has already been iterated over. Please use the
restart()
method to restart the stream.- Yield:
An iterator over the stream.
- __next__() _AnyInstance [source]#
Get the next instance in the stream.
- Returns:
The next instance in the stream.