Questions tagged [anomaly-detection]

For questions related to anomaly detection (or outlier detection) algorithms, which is the identification of rare items, events or observations which raise suspicions by differing significantly from the majority of the data. There are unsupervised, supervised and semi-supervised anomaly detection algorithms.

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Defect Detection System using Deep Learning

What is the general approach to defect detection in deep learning? Would the approach be better if we try to learn the positive images (defects in images) as much as possible or we try to learn the ...
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90 views

Is it possible to use entity embedding with autoencoder for anomaly detetction?

I'm trying to build autoencoder in keras in order to detect anomalies. However, most of the data is categorical and I have to encode it. When it comes to production, categorical features can take new ...
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99 views

Reconstruction Errors in Auto Encoders after Training

Autoencoders are used for unsupervised anomaly detection by at first learning the features of the data set with mainly "normal" data points. Then new data can be considered anomalous, if the new data ...
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106 views

Application of Blockchain in Fraud detection in stock market

I want to develop a fraud detection application in the stock market Using Blockchain technology, we have some pattern that defines the anomaly for use of supervised machine learning but there is one ...
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89 views

How to perform unsupervised anomaly detection from log file with mostly textual data?

I have a log file of the format, Index, Date, Timestamp, Module, App, Context, Session, Verbosity level, Description The log file can be considered as a master log, which consists of individual ...
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76 views

How can a de-noising auto-encoder act as an anomaly detection model?

In some research papers, I have seen that, for training the autoencoders, instead of giving the non-anomalous input images, they add some anomalies to the normal input images, and train the auto-...
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22 views

What models will you suggest to use in Industrial Anomaly Detection and Predictive analysis on live streamed data?

I have been working on industrial data, that is fed live, I want to explore a few models which might suit for this the best. The data are KPI data from the manufacturing Industry.
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14 views

How to classify anomalies between two sound datasets?

I have two sound datasets and each one has 80% normal and 20% anomalous data points. The first one is a rock song and the second one is a mellow indie song. I use half of the normal data as a baseline ...
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51 views

What are some scalable approaches to perform anomaly detection (for images with small cracks) with unsupervised learning?

I have some images with anomalies, like small cracks, but it's an imbalanced dataset. Please, suggest some effective scalable approaches. Should I consider convolutional auto-encoders? It's supposed ...
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31 views

How to deal with large number of features for Anomaly Detection

I am trying to build anomaly detection with low false positives .Dataset that i am using is a patient health sensor data. A number of parameters from the patient's sensors are collected hourly and I ...