**0**wrote:

Dear all,

That is my first experience with neural networks so I appreciate any possible help or tips.

I have a datset with 332 columns providing integer infomation, such as 0 or 1 (binary).

The last column classifies each example (row) in a superfamily. For example,

```
row 1: 0 1 0 1 0 1 0 1 0 1 0 0 0 0 0 0 0 0 Superfamily1
row 2: 0 0 0 0 0 0 1 1 1 1 0 0 0 0 0 1 1 1 Superfamily2
```

What I am trying to do is, based on the binary information (all columns except the last one), predict the Superfamily. I have a train dataset and a test one.

I have tried doing that:

```
*attach(train)
creditnet <- neuralnet(Superfamily~., train, hidden = 4, lifesign = "minimal", linear.output = FALSE, threshold = 0.1)*
```

But I get an error message:

```
*Error in terms.formula(formula) :
'.' in formula and no argument 'data'*
```

What should I do? What am I doing wrong?

Thank you in advance!