I managed to create neural network of my data. But I am not so sure about the interpretation of the R output.
I used following command to create neural network:
> net=nnet(formula = category~iplen+date_time, size=0,skip=T,lineout=T)
# weights: 3
initial value 136242.000000
final value 136242.000000
converged
Then I used following command to see the output:
> summary(net)
a 2-0-1 network with 3 weights
options were - skip-layer connections
b->o i1->o i2->o
0.64 -0.46 0.15
So from the above output Can I can conclude the following diagram of neural network?:
Second question is how can I know how useful this diagram is? I mean I wanted to find the category number(target variable) from the independent variables. so now how can I decide if this network really helped me to predict the category(target variable)? What is the final output or how to find that?
Can I conclude the following output from the above n-network? :
category= -0.46(iplen)+0.15(date_time)+0.64
Regards,
Best Answer
Your interpretation looks correct. You can check it yourself by calling
predict
on some data and comparing your calculations topredict
. I first did this in a spreadsheet, and then I calculated an R neural network using metaprogramming.By the way, the R package
neuralnet
draws nice diagrams, but apparently it supports only regression (not classification?).