KNNRegressor#
- class capymoa.regressor.KNNRegressor[source]#
Bases:
MOARegressor
K Nearest Neighbor for data stream regression with sliding window
The default number of neighbors (k) is set to 3 instead of 10 (as in MOA)
There is no specific publication for online KNN, please refer to:
Example usage:
>>> from capymoa.datasets import Fried >>> from capymoa.regressor import KNNRegressor >>> from capymoa.evaluation import prequential_evaluation >>> stream = Fried() >>> schema = stream.get_schema() >>> learner = KNNRegressor(schema) >>> results = prequential_evaluation(stream, learner, max_instances=1000) >>> results["cumulative"].rmse() 2.9811398077838542
- __init__(
- schema=None,
- CLI=None,
- random_seed=1,
- k=3,
- median=False,
- window_size=1000,
Constructing KNN Regressor.
- Parameters:
k – the number of the neighbours.
median – choose to use mean or median as the aggregation for the final prediction.
window_size – the size of the sliding window to store the instances.