Hi all,
I am trying to develop a neural network(Multilayer perceptron) with the
package 'NEURALNET'. I have some doubts on it,
1. Whether this procedure taken care about categorical input variables- The
reason is I could not find any option to describe type of variable in the
arguments?
2.The algorithm is providing input variables generalized weights like this,
> head(nn$generalized.weights[[1]])
[,1] [,2] [,3] [,4]
1 0.0088556 -0.1330079 0.1657087 0.2537842
2 0.1492874 -2.2422321 2.7934978 4.2782645
3 0.0004489 -0.0067430 0.0084008 0.0128660
4 0.0083028 -0.1247051 0.1553646 0.2379421
5 0.1071413 -1.6092161 2.0048511 3.0704457
6 0.1360035 -2.0427123 2.5449249 3.8975730
3.From this how can I interpret each input variable's relative importance
(Variable Importance)?-If yes please provide me the algorithm..
4. Is there any other neural network package providing the variable
Importance directly?
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