crfsuite-js v0.9.6

node-crfsuite

This a a fork of the node-crfsuite A nodejs binding for crfsuite

This is a link to the CRFSuite library written by Naoaki Okazaki. CRF or Conditional Random Fields are a class of statistical modeling method often applied in pattern recognition and machine learning and used for structured prediction.

Installation

For most "standard" use cases (on Mac, Linux, or Windows on a x86 or x64 processor), node-crfsuite will install nice and easy with:

npm install crfsuite --save

CRFSuite Tagger

const crfsuite = require('crfsuite')
const tagger = crfsuite.Tagger()

let is_opened = tagger.open('./path/to/crf.model')
console.log('File model is opened:', is_opened)

let tags = tagger.tag(input)
console.log('Tags: ', tags)

CRFSuite Trainer

const path = require('path')
const crfsuite = require('crfsuite')
const trainer = crfsuite.Trainer()

let model_filename = path.resolve('./model.crfsuite')

let xseq = [['walk'], ['walk', 'shop'], ['clean', 'shop']]
let yseq = ['sunny', 'sunny', 'rainy']

// submit training data to the trainer
trainer.append(xseq, yseq)
trainer.train(model_filename)

// output: ./model.crfsuite

Build from source

# clone the project
git clone https://github.com/vunb/node-crfsuite.git

# go to working folder
cd node-crfsuite

# install dependencies and tools
npm install

# build node-crfsuite from source
npm run build

# run unit-test
npm test

Travis CI - Encrypt Travis CI settings

Ref: http://rkh.github.io/travis-encrypt/public/index.html