r Neuronet软件包—多个输出

Question

The way I am currently using neural net is that it predicts one output point from many input points. More specifically, I run the below.

nn <- neuralnet(
as.formula(a ~ c + d),
data=Z, hidden=c(3,2), err.fct="sse", act.fct=custom,
linear.output=TRUE, rep=5)

Here, if Z is a matrix of columns with names a, b, c, it will predict one point from one row in column a from the corresponding points in rows c and d. (The vertical dimension is used as samples for training.)

Suppose there's also a column b. I am wondering if there's a way to predict both, a and b, from c and d? I've tried

as.formula(a+b ~ c+d)

but that does not appear to work.

Any ideas?

Answer 1

My bad, it works nicely using a + b ~ c + d. I thought the function did not accept this input (as it crashed many times), but there must have been another problem which is now gone that I cleaned it all up.

nn <- neuralnet(as.formula(a + b ~ c + d),
                data=Z, hidden=c(3,2), err.fct="sse", act.fct=custom,
                linear.output=TRUE, rep=5)

Works beautifully and returns two point (or two column) output! Neat.

---

Examples from neuralnet , the format works :)

 AND <- c(rep(0,7),1)
 OR <- c(0,rep(1,7))
 binary.data <- data.frame(expand.grid(c(0,1), c(0,1), c(0,1)), AND, OR)
 print(net <- neuralnet(AND+OR~Var1+Var2+Var3,  binary.data, hidden=0, 
         rep=10, err.fct="ce", linear.output=FALSE))