KNeighborsRegressor

Wrapper for K-Neighbors Regressor.

class KNeighborsRegressor(**kwargs)[source]

Bases: NeighborsRegressor

K-Neighbors Regressor for multidimensional approximation.

Parameters:

kwargs – arguments passed to the internal instance of KNeighborsRegressor.

Example:

>>> import numpy as np
>>> from ezyrb import KNeighborsRegressor
>>> x = np.random.uniform(-1, 1, size=(20, 2))
>>> y = np.array([np.sin(x[:, 0]), np.cos(x[:, 1])]).T
>>> knn = KNeighborsRegressor(n_neighbors=3)
>>> knn.fit(x, y)
>>> new_x = np.array([[0.5, 0.5]])
>>> y_pred = knn.predict(new_x)

Initialize a K-Neighbors Regressor.

Parameters:: kwargs – Arguments passed to sklearn’s KNeighborsRegressor.

_abc_impl = <_abc._abc_data object>