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?
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.