DecisionTree

NodeJS Implementation of Decision Tree using ID3 Algorithm. Base decision tree based on this github repo.

Features:

• Simple APIs
• Debug mode
• Inbuilt persist model capability
• Highly configurable
• Trained model can be imported/exported easily

Installation

Dillinger requires Node.js v6+ to run.

$ npm install js-decisiontree --save

How to use

const { Tree } = require('js-decisiontree');
const trainingDataSet = [];
const config = {};
const DecisionTree = new Tree(config);
DecisionTree.train(trainingDataSet, config);
DecisionTree.predict(sample);

Configuration settings

| Setting | Description | | ------ | ------ | | className | Class name or property which will be used as output of decision tree| | features | Features or data points to be used for training decision tree | | persist | If set, persists the trained model on local disk | | learn | If set, trains the model with data used for prediction | | fixMissingFeatures | If set, takes careof of missing features in training data | | debug | If set, logs the internal activity to terminal | | load | If set, loads previously stored model to local disk. This setting is only significant while intializing the tree |

APIs

| Setting | Description | | ------ | ------ | | train | Training the decision tree| | predict | Prediciting the results | | toJSON | Export the trained model as JSON | | fromJSON | Import an already trained JSON model exported using .toJSON() API |

Examples

Refer examples for exhautive examples

const DecisionTree = new Tree();
const trainingDataSet = [
    {"color":"blue", "shape":"square", "liked":false},
  	{"color":"red", "shape":"square", "liked":false},
  	{"color":"blue", "shape":"circle", "liked":true},
  	{"color":"red", "shape":"circle", "liked":true},
  	{"color":"blue", "shape":"hexagon", "liked":false},
  	{"color":"red", "shape":"hexagon", "liked":false},
  	{"color":"yellow", "shape":"hexagon", "liked":true},
  	{"color":"yellow", "shape":"circle", "liked":true}
];
const config = {
    className: 'liked',
    features: [ 'color', 'shape' ],
};
const sample = {"color":"blue", "shape":"hexagon", "liked":false }; 
DecisionTree.train(trainingDataSet, config);
const prediction = DecisionTree.predict(sample);
console.log("prediction:", prediction); // false

License

MIT

Free Software, Hell Yeah!