CT scanner for your brain.js neural network
By randomly sending inputs into a neural network, you can understand how it arrives at an output.
Note: net is an instance of brain.js
import { BrainCT, RandomInput, ValuesInput } from 'brain-ct.js'; // array index to input of net const brainCt = new BrainCT(net, [ new ValuesInput([0, 1]), new ValuesInput([0.25, 0.50, 0.75, 1]), new RandomInput(), new RandomInput(), new RandomInput(), new RandomInput() ]); // object key input of net const brainCt = new BrainCT(net, { gender: new ValuesInput([0, 1]), referrer: new ValuesInput([0.25, 0.50, 0.75, 1]), dateOfBirth: new RandomInput(), city: new RandomInput(), age: new RandomInput(), membershipExpiration: new RandomInput() });
const data = brainCt.scanSync({ iteration: 50000 }); const data = await brainCt.scan({ iteration: 50000 });
import { translate } from 'brain-ct.js'; Highcharts.chart('container', await translate.from(brainCt).to.highcharts()); Highcharts.chart('container', translate.from(brainCt).to.highchartsSync());
np
babel-node --presets=babel-preset-es2015 test.js