Issue about Autoencoder Network Architecture
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I'm having a problem with the autoencoder. I have both the encoder and decoder transfer functions for the network set to logsig. according to the formula that autoencoder runs on, the output should not be negative. However, this does happen, can you answer my query?
4 个评论
jiajun
2023-10-23
Maybe you can provide detailed formulas for the encode and decode functions, as per the example file the calculations are not consistent with the actual run.
Shreeya
2023-12-16
logsig activation function returns values between 0 and 1. Can you please elaborate why is the expected output a negative number, since the equation as shown in the image should return a positive number ?
jiajun
2023-12-16
Venu
2023-12-27
I think you have to review your network architecture, layer connectivity. Inspect the properties of each layer to ensure that the correct activation function is assigned. You can try checking Initialization of weights and biases, verify whether your input data is scaled (Normalization) properly to work well with logsig function.
回答（1 个）
Ayush Aniket
2023-12-27
0 个投票
Hi jiajun,
As per my understanding, the output from your autoencoder is negative even after setting the encoder and decoder transfer functions to 'logsig'. The reason for this occurrence is scaling of data. Since you mentioned that your input data is negative, to apply 'logsig' the 'trainAutoencoder' function scales the data to the range of the decoder activation function. This is a default 'true' parameter. Now, if the input data has been scaled, the output data is also scaled back to the initial range by the 'predict', 'encode' and 'decode' methods.
Please refer to the following documentation section link to read more about the 'ScaleData' input argument and the process of scaling:
Hope it helps.
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2023-12-27
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