# Using N columns as N classification or using 1 column with multiple values

When dealing with the Neural Network outputs, I found two different approaches to express the output to Neural Network:

### Using one column with different value as different classifications:

1        // class A
10       // class B
10       // class B
1        // class A
1        // class A


as two different class

### Using 2 columns as different classfication

1    0     // class A
1    0     // class A
0    1     // class B
1    0     // class A
0    1     // class B


Correct me if I am wrong, or please tell me the differences or which one is better for:

• MultiLayerPerceptron

• Transfer Function: TANH
• using bias neurons
• ResilentPropagation

• Using Batch Mode

Thanks.

• You use the first approach when you have two options and the second approach when you have more. Look up one-hot encoding. – Emre May 25 '17 at 6:50