From d9f78c7040de8fe2f5b667f71755c3ee1d297cba Mon Sep 17 00:00:00 2001
From: Nikolai Hartmann <Nikolai.Hartmann@physik.uni-muenchen.de>
Date: Wed, 25 Jul 2018 16:39:54 +0200
Subject: [PATCH] loss function configurable
---
toolkit.py | 12 ++++++++----
1 file changed, 8 insertions(+), 4 deletions(-)
diff --git a/toolkit.py b/toolkit.py
index 5a312a2..e801ef6 100755
--- a/toolkit.py
+++ b/toolkit.py
@@ -150,6 +150,8 @@ class ClassificationProject(object):
random data is also used for shuffling the training data, so results may vary still. To
produce consistent results, set the numpy random seed before training.
+ :param loss: loss function name
+
"""
@@ -205,7 +207,8 @@ class ClassificationProject(object):
use_modelcheckpoint=True,
modelcheckpoint_opts=None,
random_seed=1234,
- balance_dataset=False):
+ balance_dataset=False,
+ loss='binary_crossentropy'):
self.name = name
self.signal_trees = signal_trees
@@ -253,6 +256,7 @@ class ClassificationProject(object):
self.modelcheckpoint_opts = modelcheckpoint_opts
self.random_seed = random_seed
self.balance_dataset = balance_dataset
+ self.loss = loss
self.s_train = None
self.b_train = None
@@ -562,7 +566,7 @@ class ClassificationProject(object):
rn_state = np.random.get_state()
np.random.seed(self.random_seed)
self._model.compile(optimizer=optimizer,
- loss='binary_crossentropy',
+ loss=self.loss,
metrics=['accuracy'])
np.random.set_state(rn_state)
if os.path.exists(os.path.join(self.project_dir, "weights.h5")):
@@ -1031,7 +1035,7 @@ class ClassificationProject(object):
plt.plot(hist_dict['val_loss'])
plt.ylabel('loss')
plt.xlabel('epoch')
- plt.legend(['train','test'], loc='upper left')
+ plt.legend(['training data','validation data'], loc='upper left')
if log:
plt.yscale("log")
if xlim is not None:
@@ -1065,7 +1069,7 @@ class ClassificationProject(object):
plt.title('model accuracy')
plt.ylabel('accuracy')
plt.xlabel('epoch')
- plt.legend(['train', 'test'], loc='upper left')
+ plt.legend(['training data', 'validation data'], loc='upper left')
if log:
plt.yscale("log")
plt.savefig(os.path.join(self.project_dir, "accuracy.pdf"))
--
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