Rolodex
September 7, 2019, 7:19pm
1
Any idea about why, on the `neuralnet`

package, the `sse`

function for parameter: `err.fct`

divides by 2 the `Sum of Squared Errors`

?

From the document:

we have the following text:

we can ignore the `Sum`

of `H`

(outputs) and assume we only have just one output (H = 1). L corresponds to the observations.

In multiple bibliographies on internet they don't divide by 2.

Just in case, here is the `neuralnet`

package reference:

<p>Train neural networks using backpropagation,
resilient backpropagation (RPROP) with (Riedmiller, 1994) or without weight
backtracking (Riedmiller and Braun, 1993) or the modified globally
convergent version (GRPROP) by Anastasiadis et al. (2005)....

Thanks!

I cannot say whether there are some specific reasons for `neuralnet`

package, but usually this is done convenience.

When you'll be taking the derivative, you'll get a `2`

from the square term, and if you used the function with `2`

in the denominator, it gets adjusted with it.

Here's a related thread:

1 Like

Rolodex
September 8, 2019, 8:59pm
3
thank you @Yarnabrina , that helped!

system
Closed
September 15, 2019, 8:59pm
4
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