<p>You are bypassing the "hidden layer": A neural network consists of three layers: Input layer, hidden layer, and output layer:</p>

<p><img src="https://www.doc.ic.ac.uk/~nd/surprise_96/journal/vol4/cs11/report.multil.jpg"/></p>

<p>You may also have more than one hidden layer:</p>

<p><a href="https://i.sstatic.net/xqUgh.gif" rel="nofollow noreferrer"><img src="https://i.sstatic.net/xqUgh.gif" alt=""></a><br>
<sub>(source: <a href="http://www.mu-sigma.com/images/neuralNetwork.gif" rel="nofollow noreferrer">mu-sigma.com</a>)</sub>  </p>

<p>Though, in your case, since the number of hidden layers is not specified, it is safe to assume that there is just 1 hidden layer.</p>

<p>So, for example, in a 3:1 network, you have 1 output neuron, and 3 hidden neurons. The number of inputs shows the number of neurons in the input layer.</p>

CC BY-SA 2.5
2010-09-21T05:14:48.913Z
thanks, is it compulsory to have a hidden layer in a neural network?
Lazer
CC BY-SA 2.5
2010-09-21T06:00:38.027Z
You are welcome! The hidden layer is not mandatory. Though for an ANN to represent any real-world functionality, hidden layers are usually incorporated.
Sadeq Dousti
CC BY-SA 4.0
2010-09-20T18:50:36.840Z
2019-02-17T13:36:47.523Z
2019-02-17T13:36:47.523Z
Sadeq Dousti
<p>I am reading about a Neural Networks project that has some data like this</p>

<p><img src="https://i.sstatic.net/AiJb3.png" alt="alt text"></p>

<p>I am new to this, and though I think I understand what a 3:1 network mean, I do not understand what number of inputs (to each neuron) means.</p>

<p><img src="https://i.sstatic.net/xU6Eo.png" alt="alt text"></p>

<p>I think this is what a 3:1 network would look like (please correct me if I am wrong). Does 3 inputs per neuron mean that we will have 3 inputs to each of nodes A, B and C? In that case, what would the line connecting A to Z indicate? As in out of three inputs, how is a resultant chosen?</p>

<ds.algorithms><ne.neural-evol><ai.artificial-intel>
What does "number of inputs to each neuron" mean in Neural Network terms?
Lazer
# What does "number of inputs to each neuron" mean in Neural Network terms?

(Asked by: username_0 on 2010-09-20)

I am reading about a Neural Networks project that has some data like this

![alt text](https://i.sstatic.net/AiJb3.png)

I am new to this, and though I think I understand what a 3:1 network mean, I do not understand what number of inputs (to each neuron) means.

![alt text](https://i.sstatic.net/xU6Eo.png)

I think this is what a 3:1 network would look like (please correct me if I am wrong). Does 3 inputs per neuron mean that we will have 3 inputs to each of nodes A, B and C? In that case, what would the line connecting A to Z indicate? As in out of three inputs, how is a resultant chosen?

**Tags:** ds.algorithms, ne.neural-evol, ai.artificial-intel


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## 1 answers

### Answer by username_1 on 2010-09-20. Score: 7 | Accepted answer

You are bypassing the "hidden layer": A neural network consists of three layers: Input layer, hidden layer, and output layer:

![](https://www.doc.ic.ac.uk/~nd/surprise_96/journal/vol4/cs11/report.multil.jpg)

You may also have more than one hidden layer:

[![](https://i.sstatic.net/xqUgh.gif)](https://i.sstatic.net/xqUgh.gif)  
(source: [mu-sigma.com](http://www.mu-sigma.com/images/neuralNetwork.gif))

Though, in your case, since the number of hidden layers is not specified, it is safe to assume that there is just 1 hidden layer.

So, for example, in a 3:1 network, you have 1 output neuron, and 3 hidden neurons. The number of inputs shows the number of neurons in the input layer.

> **Comments:**
> **username_0**: thanks, is it compulsory to have a hidden layer in a neural network?  
> **username_1**: You are welcome! The hidden layer is not mandatory. Though for an ANN to represent any real-world functionality, hidden layers are usually incorporated.  

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