Autoencoder in R
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I am new in neural network and trying to replicate autoencoder in R from https://statslab.eighty20.co.za/posts/autoencoders_keras_r/
I received an error when executing this line:
autoencoder_model <- keras_model(inputs = input_layer, outputs = decoder)
The error is :
Error in py_call_impl(callable, dots$args, dots$keywords) :
ValueError: Graph disconnected: cannot obtain value for tensor
Tensor("input_8:0", shape=(?, 4), dtype=float32) at layer "input_8".
The following previous layers were accessed without issue:
Please let me know how can I solve this problem.
Also, I will appreciate if let me know an interpretable function in R for dimension reduction through Autoencoder.
I already found this example but I can't understand how we define the number of dimensions to be reduced, could you please explain it?
`aeNN <- autoencoder(faithful, hiddenLayers = c(4,1,4), batchSize = 5,learnRate = 1e-5, momentum = 0.5, L1 = 1e-3, L2 = 1e-3,robErrorCov = TRUE)
rX <- reconstruct(aeNN, faithful)`
neural-network keras r dimensionality-reduction autoencoder
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$begingroup$
I am new in neural network and trying to replicate autoencoder in R from https://statslab.eighty20.co.za/posts/autoencoders_keras_r/
I received an error when executing this line:
autoencoder_model <- keras_model(inputs = input_layer, outputs = decoder)
The error is :
Error in py_call_impl(callable, dots$args, dots$keywords) :
ValueError: Graph disconnected: cannot obtain value for tensor
Tensor("input_8:0", shape=(?, 4), dtype=float32) at layer "input_8".
The following previous layers were accessed without issue:
Please let me know how can I solve this problem.
Also, I will appreciate if let me know an interpretable function in R for dimension reduction through Autoencoder.
I already found this example but I can't understand how we define the number of dimensions to be reduced, could you please explain it?
`aeNN <- autoencoder(faithful, hiddenLayers = c(4,1,4), batchSize = 5,learnRate = 1e-5, momentum = 0.5, L1 = 1e-3, L2 = 1e-3,robErrorCov = TRUE)
rX <- reconstruct(aeNN, faithful)`
neural-network keras r dimensionality-reduction autoencoder
asked 1 hour ago
user9440152user9440152
11
New contributor
user9440152 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 |
$begingroup$
I am new in neural network and trying to replicate autoencoder in R from https://statslab.eighty20.co.za/posts/autoencoders_keras_r/
I received an error when executing this line:
autoencoder_model <- keras_model(inputs = input_layer, outputs = decoder)
The error is :
Error in py_call_impl(callable, dots$args, dots$keywords) :
ValueError: Graph disconnected: cannot obtain value for tensor
Tensor("input_8:0", shape=(?, 4), dtype=float32) at layer "input_8".
The following previous layers were accessed without issue:
Please let me know how can I solve this problem.
Also, I will appreciate if let me know an interpretable function in R for dimension reduction through Autoencoder.
I already found this example but I can't understand how we define the number of dimensions to be reduced, could you please explain it?
`aeNN <- autoencoder(faithful, hiddenLayers = c(4,1,4), batchSize = 5,learnRate = 1e-5, momentum = 0.5, L1 = 1e-3, L2 = 1e-3,robErrorCov = TRUE)
rX <- reconstruct(aeNN, faithful)`
neural-network keras r dimensionality-reduction autoencoder
asked 1 hour ago
user9440152user9440152
11
New contributor
user9440152 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
I am new in neural network and trying to replicate autoencoder in R from https://statslab.eighty20.co.za/posts/autoencoders_keras_r/
I received an error when executing this line:
autoencoder_model <- keras_model(inputs = input_layer, outputs = decoder)
The error is :
Error in py_call_impl(callable, dots$args, dots$keywords) :
ValueError: Graph disconnected: cannot obtain value for tensor
Tensor("input_8:0", shape=(?, 4), dtype=float32) at layer "input_8".
The following previous layers were accessed without issue:
Please let me know how can I solve this problem.
Also, I will appreciate if let me know an interpretable function in R for dimension reduction through Autoencoder.
I already found this example but I can't understand how we define the number of dimensions to be reduced, could you please explain it?
`aeNN <- autoencoder(faithful, hiddenLayers = c(4,1,4), batchSize = 5,learnRate = 1e-5, momentum = 0.5, L1 = 1e-3, L2 = 1e-3,robErrorCov = TRUE)
rX <- reconstruct(aeNN, faithful)`
neural-network keras r dimensionality-reduction autoencoder
neural-network keras r dimensionality-reduction autoencoder
asked 1 hour ago
user9440152user9440152
11
New contributor
user9440152 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 1 hour ago
user9440152user9440152
11
New contributor
user9440152 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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edited 57 mins ago
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asked 1 hour ago
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user9440152 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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asked 1 hour ago
user9440152user9440152
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asked 1 hour ago
user9440152user9440152
11
11
New contributor
user9440152 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
user9440152 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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