Unsupervised Novelty Detection Using Deep Autoencoders with Density Based Clustering
Novelty detection is a classification problem to identify abnormal patterns; therefore, it is an important task for applications such as fraud detection, fault diagnosis and disease detection. However, when there is no label that indicates normal and abnormal data, it will need expensive domain and...
Main Authors: | Tsatsral Amarbayasgalan, Bilguun Jargalsaikhan, Keun Ho Ryu |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2018-08-01
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Series: | Applied Sciences |
Subjects: | |
Online Access: | http://www.mdpi.com/2076-3417/8/9/1468 |
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