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Forecaster

PyKANForecaster

API referenceSource
Categorical in XExogenous

PyKANForecaster uses Kolmogorov Arnold Network [1] to forecast time series data.

Quickstart

python
from sktime.forecasting.pykan import PyKANForecaster

estimator = PyKANForecaster(hidden_layers=(1, 1), input_layer_size=2, grids=None, model_params=None, fit_params=None, val_size=0.5, device='cpu')

Parameters(8)

hidden_layerstuple, optional (default=(1, 1))
The number of hidden layers in the network.
input_layer_sizeint, optional (default=2)
The size of the input layer.
kint, optional (default=3)
The number of nearest neighbors to consider.
gridsnp.array, optional (default=np.array([2, 3]))
The grid sizes to use in the model.
model_paramsdict, optional (default={“k”: 2})
The parameters to pass to the model. See pykan documentation for more details.
fit_paramsdict, optional (default={“steps”: 1})
The parameters to pass to the fit method. See pykan documentation for more details.
val_sizefloat, optional (default=0.5)
The size of the validation set to use in the training.
devicestr, optional (default=”cpu”)
The device to use for training the model.

References

  1. [1 ] Liu, Ziming, et al. “KAN: Kolmogorov-Arnold Networks.” arXiv preprint arXiv:2404.19756 (2024).