All Questions
Tagged with unsupervised-learningautoencoder
14 questions
0votes
0answers
21views
About autoencoder's latent state regularity
Suppose we are dealing with the problem of dimensionality reduction of an input $\mathbf{x}\in\mathbb{R}^N$, by employing an autoencoder, as a composition of the encoder and decoder map $\mathbf{x} \...
1vote
1answer
817views
Correct approach to scale (min-max scaler) both input and output signal data for unsupervised learning?
I am working on a denoising autoencoder problem with noisy and clean signals. Before I pass the signals to my model I want to apply min-max normalization and am unsure of the correct way to apply this....
- 113
-1votes
1answer
68views
Does Anomaly Detection Algorithm works when the features are not correlated?
I am working on an Anomaly Detection Problem and the algorithm I used is an Autoencoder Multivariate Gaussian. The problem with my data is that it is unlabeled and not correlated. For example, let's ...
1vote
1answer
2kviews
How to set the Reconstruction error threshold for anomaly detection using autoencoders?
Hi I am doing anomaly detection using auto encoders.I have trained the model using 'Non Anomalous' values.Now when I give anomalous points as test data. What should be the Reconstruction error ...
- 141
3votes
1answer
246views
Is train/test-Split in unsupervised learning of neural network necessary?
I am using autoencoder for anomaly detection in warranty data. It is unsupervised. I calculate the reconstruction error by the model and the records with high reconstruction error value is considered ...
- 245
1vote
1answer
345views
More weightage to a categorical feature for an Autoencoder model
I am using autoencoder for anomaly detection. I don't have any labels already and so its unsupervised. If I have categorical variables, I usually one hot encode before giving it to the model. I would ...
- 245
10votes
1answer
187views
Robustness of ML Model in question
While trying to emulate a ML model similar to the one described in this paper, I seemed to eventually get good clustering results on some sample data after a bit of tweaking. By "good" results, I mean ...
- 201
1vote
3answers
3kviews
Cross validation for anomaly detection using autoencoder
I am using autoencoder for anomaly detection in warranty data. I don't have any ground truth labels to confirm whether the anomalies detected by the model is really an anomaly or not. Since I don't ...
- 245
1vote
0answers
2kviews
General unsupervised learning strategy when using convolutional autoencoder (CAE)
I am working on implementing an autoencoder for unsupervised learning, and I have some questions about the overall process. From what I was reading here, @rjpg suggests the following general approach: ...
- 161
13votes
3answers
24kviews
How can autoencoders be used for clustering?
Suppose I have a set of time-domain signals with absolutely no labels. I want to cluster them in 2 or 3 classes. Autoencoders are unsupervised networks that learn to compress the inputs. So given an ...
- 255
5votes
1answer
712views
Unsupervised feature reduction for anomaly detection with autoencoders
I am collecting a big number of generated numeric features for the task of unsupervised anomaly detection. I can assume that all training data is considered normal. I expect some of the generated ...
- 153
3votes
1answer
1kviews
What is the purpose of the discriminator in an adversarial autoencoder?
This is specific to the generative adversarial network (GAN) proposed in A. Makhzani et al. "Adversarial Autoencoders". In a traditional GAN, the discriminator is trained to distinguish real samples ...
- 279
2votes
1answer
8kviews
Why my loss is negative while training SAE?
I am using loss='binary_crossentropy' here is my code: I tried to increase number of training image and Epoch ,but that did not help me. ...
- 115
12votes
2answers
16kviews
Does it make sense to train a CNN as an autoencoder?
I work with analyzing EEG data, which will eventually need to be classified. However, obtaining labels for the recordings is somewhat expensive, which has led me to consider unsupervised approaches, ...
- 267
