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Hello, In the function multinom (package nnet), I get the following message after training for a model with 9 inputs and 6 classes (output) : # weights: 66 (50 variable) I understand that there are 50 variables in the model, but I...
Dear colleagues, In the function multinom (package nnet), I get the following message after training for a model with 9 inputs and 6 classes (output) : # weights: 66 (50 variable) I understand that there are 50 variables in the model, but...
I have the book by W. Venables and B. Ripley, but I didn't find the answer. Here is an explicit example : library(nnet) data(fgl) ir.glm <- multinom(type ~., data=fgl) # weights: 66 (50 variable) initial value 383.436526...
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