Open Tobias128128 opened 5 years ago
Sorry to confuse you. I used only the part to calculate the anomaly score of the paper.
2018년 12월 31일 (월) 오전 1:36, Tobias128128 notifications@github.com님이 작성:
In the article "LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection" from Malhotra are two LSTM layers (encoder and decoder) mentioned. You refered to that article and you wanted to implement that concept. But I can't see in your RNNPredictor-model that you implement two separate LSTM layer. Do you deviate from that concept intentionally or have I missed something?
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Thank you for your response. Do you think that the architecture in this paper from Malhotra is more powerful?
You mean enc-dec model is better than rnn prediction model? Yes, I assume that it is because 'reconstruction' is easier than 'prediction'.
2018년 12월 31일 (월) 오후 10:37, Tobias128128 notifications@github.com님이 작성:
Thank you for your response. Do you think that the architecture in this paper from Malhotra is more powerful?
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I‘ve implemented the lstm autoencoder model in pytorch and it seems to work great with machine data. I‘m now validating the model...
I‘ve implemented the lstm autoencoder model in pytorch and it seems to work great with machine data. I‘m now validating the model...
I have read the article 'LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection'. And interested in implementing the model to test also. could you please share with me the information(code) in detail. many thanks
I‘ve implemented the lstm autoencoder model in pytorch and it seems to work great with machine data. I‘m now validating the model...
Did you use a Sequence2Sequence like model for this?
In the article "LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection" from Malhotra are two LSTM layers (encoder and decoder) mentioned. You refered to that article and you wanted to implement that concept. But I can't see in your RNNPredictor-model that you implement two separate LSTM layer. Do you deviate from that concept intentionally or have I missed something?