8000 DOC Update notebook style for plot_bayesian_ridge_curvefit by 2357juan · Pull Request #22916 · scikit-learn/scikit-learn · GitHub
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DOC Update notebook style for plot_bayesian_ridge_curvefit #22916

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Mar 30, 2022
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DOC Update notebook style for plot_bayesian_ridge_curvefit #22916

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Update notebook style for plot_bayesian_ridge_curvefit.html
Mar 21, 2022
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Update notebook style for plot_bayesian_ridge_curvefit
Mar 21, 2022
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Update notebook style for plot_bayesian_ridge_curvefit
Mar 25, 2022
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20 changes: 12 additions & 8 deletions examples/linear_model/plot_bayesian_ridge_curvefit.py
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Expand Up @@ -28,34 +28,38 @@

# Author: Yoshihiro Uchida <nimbus1after2a1sun7shower@gmail.com>

# %%
# Generate sinusoidal data with noise
# -----------------------------------
import numpy as np
import matplotlib.pyplot as plt

from sklearn.linear_model import BayesianRidge


def func(x):
return np.sin(2 * np.pi * x)


# #############################################################################
# Generate sinusoidal data with noise
size = 25
rng = np.random.RandomState(1234)
x_train = rng.uniform(0.0, 1.0, size)
y_train = func(x_train) + rng.normal(scale=0.1, size=size)
x_test = np.linspace(0.0, 1.0, 100)


# #############################################################################
# %%
# Fit by cubic polynomial
# -----------------------
from sklearn.linear_model import BayesianRidge

n_order = 3
X_train = np.vander(x_train, n_order + 1, increasing=True)
X_test = np.vander(x_test, n_order + 1, increasing=True)
reg = BayesianRidge(tol=1e-6, fit_intercept=False, compute_score=True)

# #############################################################################
# %%
# Plot the true and predicted curves with log marginal likelihood (L)
reg = BayesianRidge(tol=1e-6, fit_intercept=False, compute_score=True)
# -------------------------------------------------------------------
import matplotlib.pyplot as plt

fig, axes = plt.subplots(1, 2, figsize=(8, 4))
for i, ax in enumerate(axes):
# Bayesian ridge regression with different initial value pairs
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