SEA#

class frouros.datasets.synthetic.SEA(seed: Optional[int] = None)#

SEA generator [street2001streaming].

References:

[street2001streaming]

Street, W. Nick, and YongSeog Kim. “A streaming ensemble algorithm (SEA) for large-scale classification.” Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining. 2001.

generate_dataset(block: int, noise: float = 0.1, num_samples: int = 12500) → Iterator[Tuple[ndarray, int]]#

Generate dataset.

Parameters:

  • block (int) – block to generate samples from

  • noise (float) – ratio of samples with a noisy class

  • num_samples (int) – number of samples to generate

Returns:

generator with the samples

Return type:

Iterator[Tuple[np.ndarray, int]]