https://github.com/clubifaximatic/node-decision-tree

Machine Learning. Decision tree implementation
https://github.com/clubifaximatic/node-decision-tree

Last synced: 4 months ago
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Machine Learning. Decision tree implementation

• Host: GitHub
• URL: https://github.com/clubifaximatic/node-decision-tree
• Owner: clubifaximatic
• License: mit
• Created: 2016-07-02T09:40:06.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2016-10-09T14:28:17.000Z (about 8 years ago)
• Last Synced: 2024-08-08T00:46:18.197Z (4 months ago)
• Language: JavaScript
• Size: 8.79 KB
• Stars: 4
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# node-decision-tree

Machine Learning. Decision tree implementation

## Implementation

A classification tree using ID3. 

## example

```js

var dt = require('node-decision-tree');

var train = [

    { class: 'crew', age: 'adult', sex: 'male', survived: 'no' },

    { class: '1st', age: 'adult', sex: 'female', survived: 'yes' },

    { class: 'crew', age: 'adult', sex: 'male', survived: 'no' },

    { class: '3rd', age: 'adult', sex: 'female', survived: 'no' },

    { class: 'crew', age: 'adult', sex: 'male', survived: 'no' },

    { class: 'crew', age: 'adult', sex: 'male', survived: 'no' },

    { class: '2nd', age: 'adult', sex: 'male', survived: 'no' },

    { class: '2nd', age: 'adult', sex: 'female', survived: 'yes' },

    { class: 'crew', age: 'adult', sex: 'male', survived: 'yes' }

];

var predict = [

    { class: 'crew', age: 'adult', sex: 'female' },

    { class: '1st', age: 'adult', sex: 'male' }

];

var test = [

    { class: 'crew', age: 'adult', sex: 'male', survived: 'no' },

    { class: '2nd', age: 'adult', sex: 'male', survived: 'no' },

    { class: '2nd', age: 'adult', sex: 'female', survived: 'no' }

];

var features = ['class', 'age', 'sex'];

var target = ['class', 'age', 'sex'];

// get dataset

var dataset = dt.Dataset('titanic');

// Create tree and fit the model

var tree = new dt.Tree;

var nodes = tree.fit(train, features, target);

// Predict

clazz = tree.predict(predict);

console.log(clazz);

// Test

var error = tree.test(test, target);

console.log(error);

```

## dataset

There is a dataset with the titanic survival model

```js

var dt = require('node-decision-tree');

var dataset = dt.dataset('titanic');

```

then it is posible to access to the training data `dataset.train`, data to predict or test `dataset.predict`, features `dataset.features` and target `dataset.target`