From 2e2344e75ad9225d4ea49af7b9cb38d528851b96 Mon Sep 17 00:00:00 2001
From: Eric Schanet <eric.schanet@cern.ch>
Date: Fri, 27 Apr 2018 17:41:21 +0200
Subject: [PATCH] Fixing ROC AUC computation
---
toolkit.py | 15 ++++++++-------
1 file changed, 8 insertions(+), 7 deletions(-)
diff --git a/toolkit.py b/toolkit.py
index f4451f3..9dfe91f 100755
--- a/toolkit.py
+++ b/toolkit.py
@@ -13,7 +13,7 @@ import pandas as pd
import h5py
from sklearn.preprocessing import StandardScaler, RobustScaler
from sklearn.externals import joblib
-from sklearn.metrics import roc_curve
+from sklearn.metrics import roc_curve, auc
from keras.models import Sequential
from keras.layers import Dense
@@ -128,7 +128,7 @@ class KerasROOTClassification:
self.b_train = tree2array(bkg_chain,
branches=self.branches+[self.weight_expr]+self.identifiers,
selection=self.selection,
- start=0, step=2)
+ start=0, step=200)
self.s_test = tree2array(signal_chain,
branches=self.branches+[self.weight_expr],
selection=self.selection,
@@ -136,7 +136,7 @@ class KerasROOTClassification:
self.b_test = tree2array(bkg_chain,
branches=self.branches+[self.weight_expr],
selection=self.selection,
- start=1, step=2)
+ start=1, step=200)
self._dump_training_list()
self.s_eventlist_train = self.s_train[self.identifiers]
@@ -404,13 +404,15 @@ class KerasROOTClassification:
logger.info("Plot ROC curve")
fpr, tpr, threshold = roc_curve(self.y_test, self.scores_test, sample_weight = self.w_test)
+
fpr = 1.0 - fpr
+ roc_auc = auc(tpr, fpr)
plt.grid(color='gray', linestyle='--', linewidth=1)
- plt.plot(fpr, tpr, label='NN')
+ plt.plot(tpr, fpr, label='NN')
plt.plot([0,1],[1,0], linestyle='--', color='black', label='Luck')
- plt.xlabel("False positive rate (background rejection)")
- plt.ylabel("True positive rate (signal efficiency)")
+ plt.xlabel("Background rejection")
+ plt.xlabel("Signal efficiency")
plt.title('Receiver operating characteristic')
plt.xlim(0,1)
plt.ylim(0,1)
@@ -421,7 +423,6 @@ class KerasROOTClassification:
plt.savefig(os.path.join(self.project_dir, "ROC.pdf"))
plt.clf()
-
def plot_score(self):
pass
--
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