what is the good combination for neural network

Question

1.00/5 (2 votes)

See more:

what is the good combination for ANN.

400, 4, 2
400, 200, 4
400, 400, 8

i really do not know how this works.. i just want to know which way gives the best output.

thanks..

Posted 11-Jul-11 7:54am

Steve Roziro

Add a Solution

Comments

#realJSOP 11-Jul-11 14:52pm

This question makes no sense at all. That's what my nueral network tells me.

1 solution

Add a Solution

Add your solution here

Treat my content as plain text, not as HTML

Preview 0

…

Existing Members

Sign in to your account

...or Join us

Download, Vote, Comment, Publish.

Your Email
Password
Forgot your password?

Your Email
This email is in use. Do you need your password?
Optional Password

I have read and agree to the Terms of Service and Privacy Policy
Please subscribe me to the CodeProject newsletters

When answering a question please:

Read the question carefully.
Understand that English isn't everyone's first language so be lenient of bad spelling and grammar.
If a question is poorly phrased then either ask for clarification, ignore it, or edit the question and fix the problem. Insults are not welcome.
Don't tell someone to read the manual. Chances are they have and don't get it. Provide an answer or move on to the next question.

Let's work to help developers, not make them feel stupid.

This content, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)

Ciumac Sergiu · Answer 1 · 2011-07-11T08:57:00

Hi There are many rule-of-thumb methods for determining the correct number of neurons to use in the hidden layers, here are just a few of them (the number of input/output units is usually known as you are aware of the them):
1) The number of hidden neurons should be between the size of the input layer and the size of the output layer.
2) The number of hidden neurons should be 2/3 the size of the input layer plus the size of the output layer.
3) The number of hidden neurons should be less than twice the size of the input layer.
Regards