# simpleneuron

> Simple neural network library for browser and Node.js

Latest version **0.0.1** (published 2018-10-09) · 0 weekly downloads

## Install

```sh
npm install simpleneuron
pnpm add simpleneuron
yarn add simpleneuron
bun add simpleneuron
```

## Health

**Score 15/100 (F)** — status: abandoned.

Positive: no vulnerabilities.

Warnings: low downloads; no types; no esm support; pre 1.0.

Negative: abandoned; low maintenance score.

## Facts

| | |
|---|---|
| Version | 0.0.1 |
| Published | 2018-10-09 |
| First published | 2014-04-27 |
| Weekly downloads | 0 |
| TypeScript types | none |
| Module format | CommonJS |
| Node | >= 0.6.0 |
| Dependencies | 0 |
| Unpacked size | 16.5 KB |
| Known vulnerabilities | 0 |
| Install scripts | no |
| GitHub stars | 5 |
| Author | Angel 'Java' Lopez |
| Maintainers | ajlopez |
| Keywords | neuron, neural network, library |

## Links

- npm: https://www.npmjs.com/package/simpleneuron
- Repository: https://github.com/ajlopez/SimpleNeuron
- Homepage: https://github.com/ajlopez/SimpleNeuron#readme
- Issues: https://github.com/ajlopez/SimpleNeuron/issues
- npm.io page: https://npm.io/package/simpleneuron

## Recent versions

- 0.0.1 (latest) — 2018-10-09
- 0.0.1-alpha — 2014-04-27

## README

# SimpleNeuron

Simple neural network library for browser and Node.js. Work in Progress.

## Installation

Via npm on Node:

```
npm install simpleneuron
```

## Usage

Reference in your program:

```js
var sn = require('simpleneuron');
```

Create a neuron
```js
var neuron = sn.neuron();
```
It is a simple threshold neuron with trigger value = 1.

Connect a neuron with other neuron
```js
var neuron = sn.neuron();
var input = sn.neuron();
neuron.input(input);
```
The input has weight 1

Connect a neuron with other neuron using a weight value
```js
var neuron = sn.neuron();
var input = sn.neuron();
neuron.input(input, -0.5);
```
The input has weight -0.5.

Set the output value of neuron:
```js
neuron.output(1);
```
Usually, this method is used to set the initial neuron layer values.

Get the output value of a neuron:
```js
var result = neuron.output();
```

Create a network of neurons, with three layers, containing 4, 15, 3 neurons. The weights
are random values between -1 and 1:
```js
var network = ss.network([4, 15, 3]);
```

Get the number of neurons in a network:
```js
var count = network.neurons();
```
In the previous created network, the count is 4+15+3 == 22.

Get the number of neurons in a layer:
```js
var count0 = network.neurons(0); // 4
var count1 = network.neurons(1); // 15
var count2 = network.neurons(2); // 3
```

TBD

## Development

```
git clone git://github.com/ajlopez/SimpleNeuron.git
cd SimpleNeuron
npm install
npm test
```

## Samples

TBD

## Versions

- 0.0.1 Published

## License

MIT

## References

- [Extreme Learning Machine](http://fastml.com/extreme-learning-machines/)
- [Backpropagation](http://en.wikipedia.org/wiki/Backpropagation)
- [Using neural nets to recognize handwritten digits](http://neuralnetworksanddeeplearning.com/chap1.html)
- [How the backpropagation algorithm works](http://neuralnetworksanddeeplearning.com/chap2.html)
- [Using neural nets to recognize handwritten digits](http://neuralnetworksanddeeplearning.com/chap1.html)
- [THE MNIST DATABASE of handwritten digits](http://yann.lecun.com/exdb/mnist/)

## Books

- Neural Networks, Simon Haykin
- Fundamentals of Deep Learning, Nikhil Buduma (2017, O�Reilly)

## Contribution

Feel free to [file issues](https://github.com/ajlopez/SimpleNeuron) and submit
[pull requests](https://github.com/ajlopez/SimpleNeuron/pulls) � contributions are
welcome<

If you submit a pull request, please be sure to add or update corresponding
test cases, and ensure that `npm test` continues to pass.

---
_Source: https://npm.io/package/simpleneuron · Machine-readable twin of the npm.io package page. Health data is recomputed on every publish._