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Results tagged with neural-networks
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user 62466
For questions about artificial networks, such as MLPs, CNNs, RNNs, LSTM, and GRU networks, their variants or any other AI system components that qualify as a neural networks in that they are, in part, inspired by biological neural networks.
2
votes
How to deal with varying number of input images?
There are are couple methods that you may wish to consider for this challenging but interesting problem.
In some cases, multiple images are captured because of artifacts in the initial images, so star …
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0
votes
Are derived or computed inputs bad for CNNs?
What you are describing could be considered feature engineering as noted by @SpiderRico, and I fully agree with his response. However, what you are describing can also be considered preprocessing. ( …
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0
votes
How are gradients of individual layers computed?
The way to "train individual layers" is to fix the weights of all other layers during training. This notebook describes an implementation of how to fix specific layers of model weights (see section F …
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1
vote
A practice neural network to find maximum values from subset
Even though (as discussed above) this problem is best handled by pre- and post-processing, yes, a neural network can be used for this problem. One possible way to do it is as follows:
Create your tr …
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0
votes
Predicting probabilities of events using neural networks
The post states that the period is exactly 1 and that there is some noise. Since you have thousands of numbers in the sequence, you should be able to construct a robust probability density function ( …
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0
votes
How do you display a neural network
Is there an easy way to display a neural network in the standard pictorial way?
Each deep learning package has easy and pictorial options for model visualization. In TensorFlow, the following model p …
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1
vote
why validation accuracy be greater than training accuracy for deep learning models?
Why validation accuracy be greater than training accuracy for deep learning models?
You are probably thinking that the training process is supposed to reduce the training loss (and increase training a …
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1
vote
Accepted
How to embed quantitative variables?
Is there a common best practice for what I am trying to do?
No, there are no best practices for what you are trying to do. Your categorical variables, time series, and numeric variables don't have to …
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0
votes
Dummy variable trap in neural networks and class visualization
Assume that you have a (3, 3) dataset (3 records, 3 variables), and a, b, and c are alpha, beta, and gamma, respectively. Then, an example dataframe would be as follows:
A B C
1 a b b
2 a a b
…
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1
vote
How can I use my neural network model, trained on MNIST database, on "real word" digits such...
Can I test my model on other digits, for example I write the digit 7 on a paper with my pen and check whether my model would recognize it or not? How can I do it?
Yes, definitely. One of the main goa …
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0
votes
Which other loss functions for hierarchical multi-label classification could I use?
What hierarchical loss functions are worth trying
There are a number of hierarchical loss functions that have been described (see articles #1 and #2), such as hierarchical win and normalized LCA. Th …
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1
vote
Accepted
Single label classification into hierarchical categories using a neural network
In my opinion, the problem you pose is best described as an ordinal classification problem, rather than a hierarchical classification problem. There are a number of approaches (besides ordinal loss f …
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