const array = require('lodash/array'); const { MKT } = require('@mkt-eg/mkt') const MKT = new MKT('bbbc22c3a13c74456a6d4bb7ba5745476ebfdc81c867fc240258122b78eb6a6f') MKT.historical({ sympolPrice: 'true', e: 'CCCAGG', fsym: 'BTC', tsyms: 'USD', type: 'single', aggregate: '1', aggregatePredictableTimePeriods: true, limit: 30, allData: 'false', extraParams: 'NotAvailable', sign: 'false', apiType: 'day' }).then((results)=>{ const data = JSON.stringify(results.data) const options = { rawData:data, chunkSize:5,// split data into 5 series array forcastList:array.chunk(rawData,5)[3], // Get The last series from data. steps:30, // predicit the next 30 days NNOptions: { inputSize: 4, hiddenLayers: [4,4], outputSize: 4, learningRate: 0.01, decayRate: 0.999, }, trainOptions:{ iterations: 20000, // the maximum times to iterate the training data --> number greater than 0 errorThresh: 0.005, // the acceptable error percentage from training data --> number between 0 and 1 log: true, // true to use console.log, when a function is supplied it is used --> Either true or a function logPeriod: 10, // iterations between logging out --> number greater than 0 learningRate: 0.3, // scales with delta to effect training rate --> number between 0 and 1 momentum: 0.1, // scales with next layer's change value --> number between 0 and 1 callback: null, // a periodic call back that can be triggered while training --> null or function callbackPeriod: 10, // the number of iterations through the training data between callback calls --> number greater than 0 timeout: Infinity // the max number of milliseconds to train for --> number greater than 0 } } console.log(MKT.predict(options)) })
$ npm i @mkt-eg/mkt
6,096 coin , 283,037 TRADING PAIRS and more can be explored it
31 News Provider, where you can simulate human feelings in the markets
This Project is built with Tensorflow.js core , 14 sec stock prediction , 3 lines of code
Encrypt your predictions and save it. No one can get to your models !
There will be a specific version of the front end to make the experience easier for web developers
The library will support the plugins from the developers and will create a library for all models and their results to be presented to the public
Read our documentation for advanced customization
Documentation