lc = learn_curve(X,y,10000)
print(f'Cross Validation Accuracies:\n{"-"*25}\n{list(lc["cv_scores"])}\n\n\
Mean Cross Validation Accuracy:\n{"-"*25}\n{np.mean(lc["cv_scores"])}\n\n\
Standard Deviation of Cross Validation Accuracy:\n{"-"*25}\n{np.std(lc["cv_scores"])} (High Variance)\n\n\
Training Accuracy:\n{"-"*15}\n{lc["train_score"]}\n\n')
sns.lineplot(data=lc["learning_curve"],x="Training_size",y="value",hue="variable")
plt.title("Learning Curve of an Overfit Model")
plt.ylabel("Misclassification Rate/Loss");