plot_learning_curve with examples#
An example showing the plot_learning_curve
function
used by a scikit-learn classifier.
# Authors: The scikit-plots developers
# SPDX-License-Identifier: BSD-3-Clause
from sklearn.datasets import (
load_digits as data_10_classes,
)
from sklearn.linear_model import LogisticRegression
import numpy as np
np.random.seed(0) # reproducibility
# importing pylab or pyplot
import matplotlib.pyplot as plt
# Import scikit-plot
import scikitplot as sp
# Load the data
X, y = data_10_classes(return_X_y=True, as_frame=False)
# Create an instance of the LogisticRegression
model = LogisticRegression(max_iter=int(1e5), random_state=0)
# Plot!
ax = sp.estimators.plot_learning_curve(
model,
X,
y,
save_fig=True,
save_fig_filename="",
# overwrite=True,
add_timestamp=True,
# verbose=True,
)

Total running time of the script: (0 minutes 4.384 seconds)
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