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I'm using Orange Data Mining in a regression analysis applying Artificial Neural Network (ANN). Some works suggest defining the number of neurons in the input layer as the number of variables. The Orange ANN uses sklearn’s Multi-layer Perceptron algorithm (MLP); however, I can only set the number of neurons per hidden layer (e.g., 4, 3 and 2; tree layers with 4, 3 and 2 neurons). Should I assume a hidden layer as the input layer and set the number of neurons as variable numbers? Does the MLP set the input layer automatically?

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I am not familiar with the software you are using, but the number of neurons on the input layer depends on the number of features in the data. What follows, the software can just count the columns and use them to set the number of neurons on the input layer. The hidden layer is not an input layer, it is unlikely for them to name things in a way that confuses those two types of layers.

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  • $\begingroup$ thanks of your answer. Maybe I wasn’t clear enough. So let me try to clarify. Orange name the parameters correctly, you can check this in this orange3.readthedocs.io/projects/orange-visual-programming/en/…. My doubt is if I can use the hidden layer as the input one due to the absence of a specific parameter in sklearn’s Multi-layer Perceptron algorithm (MLP), which is used in Orange. As you commented, I understand that hidden layer is not an input layer. Thus, I should not set a hidden layer as the number of features :) $\endgroup$ – kvratto Jun 21 at 13:07
  • $\begingroup$ @kvratto How exactly would you use it as an input layer? It will set up the input layer by itself unless I am missing something about the software itself. $\endgroup$ – Tim Jun 21 at 13:08
  • $\begingroup$ I didn't find if the sklearn’s Multi-layer Perceptron algorithm (and consequently Orange) set up the input layer by itself. I thought the algorithm just skipped this step (set up the input layer) or ran with a number of neurons in the standard input layer. I truly appreciate your comments. $\endgroup$ – kvratto Jun 21 at 13:20

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