Sat Jun 17 06:28:57 2023

wave_regression_knn():
  Python version: 3.8.10
  scikit-learn version: 1.2.2

  Generate the wave dataset, (X, y).
  X.shape: (40, 1)
  Plot the dataset.
  Graphics saved as 'wave_regression_data.png'
  Demonstrate k-nearest-neighbors with k = 1.
  Graphics saved as 'wave_regression_k1.png'
  Demonstrate k-nearest-neighbors with k = 3.
  Graphics saved as 'wave_regression_k3.png'

Test set predictions:
[-0.05396539  0.35686046  1.13671923 -1.89415682 -1.13881398 -1.63113382
  0.35686046  0.91241374 -0.44680446 -1.13881398]
Test set R^2:
0.8344172446249605

Plot predictions for all possible values of feature:
  Graphics saved as "wave_regression_all.png"

  Produce linear regression coefficients y = w[0] * x + b
w[0]: 0.393906  b: -0.031804

wave_regression_knn():
  Normal end of execution.
Sat Jun 17 06:28:59 2023