<p>The number of dimensions is a hyperparameter of your model, and you should do a hyperparameter search, like with any other parameters. There's also a tradeoff between dimension and training speed, so it should be small enough to be trainable in a reasonable time.</p>

CC BY-SA 4.0
2018-12-28T16:14:25.487Z
2019-12-26T15:31:10.470Z
2019-12-26T15:31:10.470Z
Konstantin Solomatov
<p>How should we choose the dimensions of the encoding layer in auto-encoders?</p>

<neural-networks><autoencoders><hyperparameter-optimization><variational-autoencoder><hyper-parameters>
How should we choose the dimensions of the encoding layer in auto-encoders?
Neha soni
# How should we choose the dimensions of the encoding layer in auto-encoders?

(Asked by: username_0 on 2018-12-27)

How should we choose the dimensions of the encoding layer in auto-encoders?

**Tags:** neural-networks, autoencoders, hyperparameter-optimization, variational-autoencoder, hyper-parameters


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## 1 answers

### Answer by username_1 on 2018-12-28. Score: 3

The number of dimensions is a hyperparameter of your model, and you should do a hyperparameter search, like with any other parameters. There's also a tradeoff between dimension and training speed, so it should be small enough to be trainable in a reasonable time.


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