Example: Nearest Neighbors regression
Nearest Neighbors regression
Demonstrate the resolution of a regression problem using a k-Nearest Neighbor and the interpolation of the target using both barycenter and constant weights.
print(__doc__) # Author: Alexandre Gramfort <alexandre.gramfort@inria.fr> # Fabian Pedregosa <fabian.pedregosa@inria.fr> # # License: BSD 3 clause (C) INRIA
Generate sample data
import numpy as np import matplotlib.pyplot as plt from sklearn import neighbors np.random.seed(0) X = np.sort(5 * np.random.rand(40, 1), axis=0) T = np.linspace(0, 5, 500)[:, np.newaxis] y = np.sin(X).ravel() # Add noise to targets y[::5] += 1 * (0.5 - np.random.rand(8))
Fit regression model
n_neighbors = 5
for i, weights in enumerate(['uniform', 'distance']):
knn = neighbors.KNeighbo