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ROC曲線とAUCの出力

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PythonでROC曲線を描画してみた

前提

  1. Python
  2. ロジスティック回帰で予測値出力済み
  3. scikit-learnとmatplotlibを使う

コード

roc.py
from sklearn import metrics
import matplotlib.pyplot as plt
import numpy as np

# FPR, TPR(, しきい値) を算出
fpr, tpr, thresholds = metrics.roc_curve(test_y, predict_y)

# ついでにAUCも
auc = metrics.auc(fpr, tpr)

# ROC曲線をプロット
plt.plot(fpr, tpr, label='ROC curve (area = %.2f)'%auc)
plt.legend()
plt.title('ROC curve')
plt.xlabel('False Positive Rate')
plt.ylabel('True Positive Rate')
plt.grid(True)

roc_curve.png

参考

ROC曲線とAUCについてはこちらを参考に。

【統計学】ROC曲線とは何か、アニメーションで理解する。
【ROC曲線とAUC】機械学習の評価指標についての基礎講座

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