How to Decide size of Neural Network like number of neurons in a hidden layer & Number of hidden layers?

Hi friends, I want to design a neural network which should give one output with five inputs and i have input samples are 432. So please suggest how to design neural network and which type of neural network i should and how to decide number of hidden layers and no of neurons in each hidden layer.

Answer 1

[Greg Heath]

Use 1 hidden layer.

Use fitnet for curve-fitting or regression.

Use patternnet for pattern-recognition or classification. For c categories with indices 1:c, the target matrix should contain columns of eye(c). The relationship between target columns and class indices is target = ind2vec(classindices) and classindices = vec2ind(target). Since since the sum of the target columns is 1, one of the rows (usually the last) can be omitted. This reduction is used mostly when c=2.

Find a good value for the number of hidden nodes, H, by trial and error. Create numH*Ntrials nets in a double loop: An outer loop H = Hmin:dH:Hmax over number of hidden nodes and an inner loop i = 1: Ntrials over number of random trn/val/tst data divisions and random weight initialization trials for each value of H.

I typically use numH ~ 10, Ntrials ~ 10 and tabulate results in Ntrials X numH matrices.

Many examples can be obtained by searching the NEWSGROUP and ANSWERS using the keywords

Greg Ntrials Nw

Hope this helps.

Thank you for formally accepting my answer

Greg

Answer 2

[Nduwamungu Corneille]

You may get more details on how many hidden layers and nodes in the following article: http://www.tandfonline.com/doi/abs/10.1080/01431160802549278#.Uazyu0CW_ng

Hope this helps.

Answer 3

[abhishek aggarwal]

Go to the given link. It may help you. www.ijettjournal.org/volume-3/issue-6/IJETT-V3I6P206.pdf

[Jeong_evolution]

Thank you for your share !