https://github.com/yovanoc/synaps

TypeScript Neural Network Library
https://github.com/yovanoc/synaps

Last synced: about 1 month ago
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TypeScript Neural Network Library

• Host: GitHub
• URL: https://github.com/yovanoc/synaps
• Owner: yovanoc
• License: mit
• Created: 2017-10-18T11:04:41.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2017-12-09T00:47:21.000Z (about 7 years ago)
• Last Synced: 2024-01-05T07:05:26.006Z (about 1 year ago)
• Language: TypeScript
• Size: 69.3 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Synaps

TypeScript Neural Network Library

## Installation

 * In the browser

   ```html

   

   ```

 * In Node.js

   ```

   $ npm install synaps

   ```

   and

   ```javascript

   const synaps = require("synaps").default;

   ```

   or in es6 or TypeScript

   ```javascript

   import synaps from "synaps";

   ```

## Usage

 * Creating a new instance

   * Neural network with 3 input neurons and 1 output neuron

     ```javascript

     let network = new synaps.Network.Type.FeedForward(3, [], 1);

     ```

   * Neural network with 4 input neurons, 3 hidden neurons and 2 output neurons

     ```javascript

     let network = new synaps.Network.Type.FeedForward(4, [ 3 ], 2);

     ```

   * Neural network with 6 input neurons, two hidden layers with 4 and 2 neurons, and 3 output neurons

     ```javascript

     let network = new synaps.Network.Type.FeedForward(6, [ 4, 2 ], 3);

     ```

 * Passing any number of additional options to the network

   ```javascript

   // pass an object containing the desired options as the fourth parameter

   let network = new synaps.Network.Type.FeedForward(3, [ 4 ], 1, {

       seed: 501935,

       learningRate: 0.3,

       hiddenLayerActivationFunction: new synaps.Activation.HyperbolicTangent(),

       outputLayerActivationFunction: new synaps.Activation.BinaryStep()

   });

   ```

 * Available activation functions

   ```javascript

   new synaps.Activation.ArcTangent();

   new synaps.Activation.BinaryStep();

   new synaps.Activation.GaussianFunction();

   new synaps.Activation.HyperbolicTangent();

   new synaps.Activation.Identity();

   new synaps.Activation.LogisticFunction();

   new synaps.Activation.RectifiedLinearUnit();

   new synaps.Activation.RectifiedLinearUnit(0.01);

   new synaps.Activation.SinusoidFunction();

   ```

 * Training the network using supervised batch ("all-at-once") learning

   ```javascript

   // the first parameter is the array of inputs and the second parameter is the array of desired outputs

   // the third parameter is the optional number of iterations and the fourth parameter is the optional error threshold

   let error = network.trainBatch(

       [

           [0, 0, 1],

           [0, 1, 1],

           [1, 0, 1],

           [1, 1, 1]

       ],

       [

           [ 0 ],

           [ 1 ],

           [ 1 ],

           [ 0 ]

       ],

       60000,

       0.005

   );

   ```

 * Training the network using supervised online ("single-pattern") learning

   ```javascript

   // the first parameter is the input and the second parameter is the desired output

   let error = network.train([0, 0, 1], [ 0 ]);

   ```

 * Asking the network to predict some output from a supplied input pattern

   ```javascript

   // the single parameter is the input to process

   network.predict([ 0, 0, 1 ])

   ```

 * Saving the network with all its properties to a JSON string

   ```javascript

   let jsonStr = JSON.stringify(network);

   ```

 * Restoring the network with all its properties from a JSON string

   ```javascript

   let network = synaps.Network.Type.FeedForward.fromJson(jsonStr);

   ```

## Development

 * Prerequisites

   ```

   $ npm install

   ```

* Lint the js files

    ```

    $ npm lint

    ```

    or to fix some errors automatically

    ```

    $ npm lint:fix

    ```  

* Build the js files

    ```

    $ npm build

    ```  

 * Running the Node.js examples

   ```

   $ node examples/node.js

   ```

## Contributing

All contributions are welcome! If you wish to contribute, please create an issue first so that your feature, problem or question can be discussed.

### Socials Links

- [Discord](https://discord.gg/hUTW6jQ)

- [Slack](https://join.slack.com/t/synapsworkspace/shared_invite/enQtMjU4NjU4NzgwNDY2LWU4M2I0MWFlYzYxYzVjMjIyMzdkOTAzNDc4MzI4ZDAzM2ExYmVmYWIzZTAzMDcwNGFiZjNiOWQzNzkxNWEwYWQ)