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import spacy
from spacy import displacy
from sklearn.metrics import precision_recall_curve
import matplotlib.pyplot as plt

# 鍔犺浇鏁版嵁闆?/span>
# Assume `y_true` contains true labels and `y_pred` contains predicted labels
y_true = [0, 1, 1, 0]
y_scores = [0.1, 0.9, 0.8, 0.3]

# 璁＄畻绮剧‘鐜囧拰鍙洖鐜?/span>
precision, recall, _ = precision_recall_curve(y_true, y_scores)

# 缁樺埗PR鏇茬嚎
plt.figure()
plt.step(recall, precision, color='b', alpha=0.2, where='post')
plt.fill_between(recall, precision, alpha=0.2, color='b')
plt.xlabel('Recall')
plt.ylabel('Precision')
plt.ylim([0.0, 1.05])
plt.xlim([0.0, 1.0])
plt.title('Precision-Recall curve')
plt.show()

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