code: def validation_curve_sklearn_example(
      path="images/validation_curve_sklearn_example.png",
  ):
      digits = load_digits()
      X, y = digits.data, digits.target
  
      _, ax = plt.subplots()
  
      param_range = np.logspace(-6, -1, 5)
      oz = ValidationCurve(
          SVC(),
          ax=ax,
          param_name="gamma",
          param_range=param_range,
          logx=True,
          cv=10,
          scoring="accuracy",
          n_jobs=4,
      )
      oz.fit(X, y)
      oz.show(outpath=path)
  
file_path: yellowbrick/docs/api/model_selection/validation_curve.py
imports: import numpy
  import matplotlib.pyplot
  from sklearn.svm import SVC
  from sklearn.datasets import load_digits
  from sklearn.preprocessing import OneHotEncoder
  from sklearn.neighbors import KNeighborsClassifier
  from sklearn.model_selection import StratifiedKFold
  from yellowbrick.datasets import load_game
  from yellowbrick.model_selection import ValidationCurve
label_desc: Use image node_id 1 for calling a global function with example usage: validation_curve_sklearn_example(path) without return types