neuralNetworkProcedural.js

exports.start = function (res) { // res is the Express response object, being the server package I used
    let training = true
    let trainingDataSet = []
    let testResult = []
    const network = new NN.NeuralNetwork();
    let dataTypes = []
    let listOfTrainingData = []
    let listOfTestData = []
    let trainingDataRaw = []
    let testDataRaw = []
    var parser = csv({ delimiter: ',' }, function (err, data) {
        if (err) {
            return null
        } else {
            data.forEach(function (element, index) { // data[][] represents elements of each row in the CSV
                if (index === 0) {
                    // header row
                    element.forEach(function (header) {
                        dataTypes.push(header)
                    })
                } else {
                    if(element[0] === 'TEST') {
                        // flag start of test data
                        training = false
                    } else { // last 3 rows (elements) of data[][] are test data
                        if(training) {
                            listOfTrainingData.push(element[0]) // first element is a unique designator, not data (is for user feedback)
                            trainingDataRaw.push(element.slice(1))
                        } else {
                            listOfTestData.push(element[0]) // designator
                            testDataRaw.push(element.slice(1))
                        }
                    }
                }
            })
            trainingDataRaw.forEach((data) => {
                const input = data.slice(0, data.length - 1)
                const output = data.slice(data.length - 1)
                trainingDataSet.push({ input: input, output: output })
            })
            network.train(trainingDataSet, { /* some config settings */ })
            testDataRaw.forEach((dataPoint) => {
                const input = dataPoint.slice(0, dataPoint.length - 1)
                const output = dataPoint.slice(dataPoint.length - 1)
                testResult.push({ actual: network.run(input), desired: output })
            })
        }
    })
    try {
        const stream = fs.createReadStream(path.join(__dirname, 'data.csv'))
        stream.pipe(parser)
        stream.on('close', () => {
            res.send(testResult)
        })
        stream.on('error', (error) => {
            throw(error)
        })
    } catch (err) {
        res.send(err)
    }
}