%load_ext autoreload
%autoreload 2
%matplotlib inline
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
plt.rcParams['figure.figsize'] = [14, 9]
from sklearn_plot_api import plot_learning_curve
from sklearn.datasets import load_digits
from sklearn.naive_bayes import GaussianNB
from sklearn.model_selection import ShuffleSplit
cv = ShuffleSplit(n_splits=100, test_size=0.2, random_state=0)
estimator = GaussianNB()
digits = load_digits()
X, y = digits.data, digits.target
viz = plot_learning_curve(estimator, X, y, n_jobs=4, cv=cv)
viz.train_fill_between_.set_color('red')
viz.train_line_.set_color('red')
viz.ax_.legend()
viz.figure_
viz.plot()
<sklearn_plot_api.learning_curve.LearningCurveViz at 0x11269da20>