Fraud detection using auto-encoders and Keras
1
$begingroup$
I am following this example to learn a bit about the use of auto-encoders in fraud detection.
Now that I reached the end of the article, two questions rose in mind:
- Can we train the network in an unsupervised way, freeze the layers weights, add a sigmoid layer as an output then finally use this model as a binary classifier?
- Are auto-encoders considered as the state-of-the-art method in fraud detection? What other alternatives can be used in this case?
classification keras unbalanced-classes
edited yesterday
Majid Mortazavi
1,8101326
asked Mar 16 '18 at 16:47
ChiPlusPlusChiPlusPlus
123111
$endgroup$
add a comment |
1
$begingroup$
I am following this example to learn a bit about the use of auto-encoders in fraud detection.
Now that I reached the end of the article, two questions rose in mind:
- Can we train the network in an unsupervised way, freeze the layers weights, add a sigmoid layer as an output then finally use this model as a binary classifier?
- Are auto-encoders considered as the state-of-the-art method in fraud detection? What other alternatives can be used in this case?
classification keras unbalanced-classes
edited yesterday
Majid Mortazavi
1,8101326
asked Mar 16 '18 at 16:47
ChiPlusPlusChiPlusPlus
123111
$endgroup$
$begingroup$
Do layer-wise training like Hinton for Deep Belief Networks, and then train a classifier with the internal representation
$endgroup$
– Andrea Guidi
yesterday
add a comment |
1
1
1
$begingroup$
I am following this example to learn a bit about the use of auto-encoders in fraud detection.
Now that I reached the end of the article, two questions rose in mind:
- Can we train the network in an unsupervised way, freeze the layers weights, add a sigmoid layer as an output then finally use this model as a binary classifier?
- Are auto-encoders considered as the state-of-the-art method in fraud detection? What other alternatives can be used in this case?
classification keras unbalanced-classes
edited yesterday
Majid Mortazavi
1,8101326
asked Mar 16 '18 at 16:47
ChiPlusPlusChiPlusPlus
123111
$endgroup$
I am following this example to learn a bit about the use of auto-encoders in fraud detection.
Now that I reached the end of the article, two questions rose in mind:
- Can we train the network in an unsupervised way, freeze the layers weights, add a sigmoid layer as an output then finally use this model as a binary classifier?
- Are auto-encoders considered as the state-of-the-art method in fraud detection? What other alternatives can be used in this case?
classification keras unbalanced-classes
classification keras unbalanced-classes
edited yesterday
Majid Mortazavi
1,8101326
asked Mar 16 '18 at 16:47
ChiPlusPlusChiPlusPlus
123111
edited yesterday
Majid Mortazavi
1,8101326
asked Mar 16 '18 at 16:47
ChiPlusPlusChiPlusPlus
123111
edited yesterday
Majid Mortazavi
1,8101326
edited yesterday
Majid Mortazavi
1,8101326
edited yesterday
Majid Mortazavi
1,8101326
1,8101326
asked Mar 16 '18 at 16:47
ChiPlusPlusChiPlusPlus
123111
asked Mar 16 '18 at 16:47
ChiPlusPlusChiPlusPlus
123111
asked Mar 16 '18 at 16:47
ChiPlusPlusChiPlusPlus
123111
123111
$begingroup$
Do layer-wise training like Hinton for Deep Belief Networks, and then train a classifier with the internal representation
$endgroup$
– Andrea Guidi
yesterday
add a comment |
$begingroup$
Do layer-wise training like Hinton for Deep Belief Networks, and then train a classifier with the internal representation
$endgroup$
– Andrea Guidi
yesterday
$begingroup$
Do layer-wise training like Hinton for Deep Belief Networks, and then train a classifier with the internal representation
$endgroup$
– Andrea Guidi
yesterday
$begingroup$
Do layer-wise training like Hinton for Deep Belief Networks, and then train a classifier with the internal representation
$endgroup$
– Andrea Guidi
yesterday
add a comment |
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$begingroup$
Do layer-wise training like Hinton for Deep Belief Networks, and then train a classifier with the internal representation
$endgroup$
– Andrea Guidi
yesterday