LSTM Autoencoder on Patterns of Labels
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Currently, I am trying to do anomaly detection on univariate data consisting of labels. For example: [A, A, B, C] is good but [A, A, A, A] is anomalous. I'm dealing with more than just ABC. Is an LSTM Autoencoder a valid approach? If so, how should go about prepping the data and a threshold value to determine an anomaly?
I've tried a more regression based approach by turning all the labels into numbers, scaling them, then going through the normal steps of training and testing the model. I feel as though this isn't the best solution to the problem since my data is not continuous like EEG data.
machine-learning deep-learning lstm rnn autoencoder
asked 2 hours ago
Adrian PerezAdrian Perez
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$begingroup$
Currently, I am trying to do anomaly detection on univariate data consisting of labels. For example: [A, A, B, C] is good but [A, A, A, A] is anomalous. I'm dealing with more than just ABC. Is an LSTM Autoencoder a valid approach? If so, how should go about prepping the data and a threshold value to determine an anomaly?
I've tried a more regression based approach by turning all the labels into numbers, scaling them, then going through the normal steps of training and testing the model. I feel as though this isn't the best solution to the problem since my data is not continuous like EEG data.
machine-learning deep-learning lstm rnn autoencoder
asked 2 hours ago
Adrian PerezAdrian Perez
1
New contributor
Adrian Perez is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
Currently, I am trying to do anomaly detection on univariate data consisting of labels. For example: [A, A, B, C] is good but [A, A, A, A] is anomalous. I'm dealing with more than just ABC. Is an LSTM Autoencoder a valid approach? If so, how should go about prepping the data and a threshold value to determine an anomaly?
I've tried a more regression based approach by turning all the labels into numbers, scaling them, then going through the normal steps of training and testing the model. I feel as though this isn't the best solution to the problem since my data is not continuous like EEG data.
machine-learning deep-learning lstm rnn autoencoder
asked 2 hours ago
Adrian PerezAdrian Perez
1
New contributor
Adrian Perez is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
Currently, I am trying to do anomaly detection on univariate data consisting of labels. For example: [A, A, B, C] is good but [A, A, A, A] is anomalous. I'm dealing with more than just ABC. Is an LSTM Autoencoder a valid approach? If so, how should go about prepping the data and a threshold value to determine an anomaly?
I've tried a more regression based approach by turning all the labels into numbers, scaling them, then going through the normal steps of training and testing the model. I feel as though this isn't the best solution to the problem since my data is not continuous like EEG data.
machine-learning deep-learning lstm rnn autoencoder
machine-learning deep-learning lstm rnn autoencoder
asked 2 hours ago
Adrian PerezAdrian Perez
1
New contributor
Adrian Perez is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 2 hours ago
Adrian PerezAdrian Perez
1
New contributor
Adrian Perez is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 2 hours ago
Adrian PerezAdrian Perez
1
New contributor
Adrian Perez is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 2 hours ago
Adrian PerezAdrian Perez
1
asked 2 hours ago
Adrian PerezAdrian Perez
1
1
New contributor
Adrian Perez is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Adrian Perez is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
Adrian Perez is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
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Adrian Perez is a new contributor. Be nice, and check out our Code of Conduct.
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