roc curve
#ROC curve code snippet from external source(Module notes)
def draw_roc( actual, probs ):
fpr, tpr, thresholds = metrics.roc_curve( actual, probs,
drop_intermediate = False )
auc_score = metrics.roc_auc_score( actual, probs )
plt.figure(figsize=(5, 5))
plt.plot( fpr, tpr, label='ROC curve (area = %0.2f)' % auc_score )
plt.plot([0, 1], [0, 1], 'k--')
plt.xlim([0.0, 1.0])
plt.ylim([0.0, 1.05])
plt.xlabel('False Positive Rate or [1 - True Negative Rate]')
plt.ylabel('True Positive Rate')
plt.title('Receiver operating characteristic example')
plt.legend(loc="lower right")
plt.show()
return None
fpr, tpr, thresholds = metrics.roc_curve( y_train_pred_final.Converted, y_train_pred_final.Converted_prob, drop_intermediate = False )
draw_roc(y_train_pred_final.Converted, y_train_pred_final.Converted_prob)