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[Python] GINI, KS, Plotting ROC curve
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from sklearn.metrics import roc_curve, roc_auc_score, auc | |
from scipy import stats | |
import matplotlib.pyplot as plt | |
# %matplotlib inline | |
def plot_roc_curve(y, y_pred, gini, ks): | |
fpr, tpr, thresholds = roc_curve(y, y_pred) | |
roc_auc = auc(fpr, tpr) | |
fig = plt.figure() | |
plt.plot(fpr, tpr, 'b--', label='%s AUC = %0.4f, GINI = %0.2f, KS = %s' % ('Model: ', roc_auc, gini, ks)) | |
plt.plot([0, 1], [0, 1], 'k--') | |
plt.xlim([0.0, 1.0]) | |
plt.ylim([0.0, 1.0]) | |
plt.xlabel('False Positive Rate') | |
plt.ylabel('True Positive Rate') | |
plt.legend(loc=0, fontsize='small') | |
plt.show() | |
gini = 2 * roc_auc_score(df['y'], df['y_pred']) - 1 | |
ks = stats.ks_2samp(df[df['y'] == 0]['y_pred'], df[df['y'] == 1]['y_pred']).statistic | |
print('GINI = %s, KS = %s' % (gini, ks)) | |
plot_roc_curve(y, y_pred, gini, ks) |
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