Created
May 9, 2019 18:56
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# Have 1d array-likes y_true and y_pred. | |
# y_true is expected to be 0/1, | |
# and y_pred is expected to have floats in [0, 1]. | |
# | |
# I learned how to do this from here: | |
# https://scikit-learn.org/stable/auto_examples/model_selection/plot_precision_recall.html | |
from sklearn.metrics import average_precision_score | |
from sklearn.metrics import precision_recall_curve | |
prec, recall, _ = precision_recall_curve(y_true, y_pred) | |
avg_prec = average_precision_score(y_true, y_pred) | |
plt.step(recall, prec, color='b', alpha=0.2, where='post') | |
plt.fill_between(recall, prec, 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('2-class Precision-Recall curve: AP={0:0.2f}'.format(avg_prec)) | |
plt.show() |
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