gradient descent in kotlin

findLearningParametersHollow.kt

 fun findLearningParameters(videoGameData: Array<Pair<Double, Double>>): Pair<Double, Double> {
        //...
        return Pair(m, b)
    }

GradientDescent.kt

import com.squareup.moshi.JsonAdapter
import com.squareup.moshi.Moshi
import com.squareup.moshi.Types
import org.junit.Test
import kotlin.math.pow


class Tests {
    fun updateGuess(
        guess: Pair<Double, Double>,
        learningRate: Double,
        videoGameData: Array<Pair<Double, Double>>
    ): Pair<Double, Double> {
        val (m, b)  = guess
        val mGradient = videoGameData.fold(0.0) { acc: Double, pair: Pair<Double, Double> ->
            val (x, y) = pair
            acc + ((((m * x) + b) - y) * x)
        } / videoGameData.size
        val bGradient = videoGameData.fold(0.0) { acc: Double, pair: Pair<Double, Double> ->
            val (x, y) = pair
            acc + ((((m * x) + b) - y))
        } / videoGameData.size
        val newM = m - (learningRate * mGradient)
        val newB = b - (learningRate * bGradient)
        return Pair(newM, newB)
    }

    fun cost(videoGameData: Array<Pair<Double, Double>>, learningParameters: Pair<Double, Double>): Double =
        videoGameData.fold(0.0) { acc: Double, pair: Pair<Double, Double> ->
            val (m, b) = learningParameters
            val (x, y) = pair
            acc + ((((m * x) + b) - y).pow(2)/2)
        } / videoGameData.size

    fun findLearningParameters(videoGameData: Array<Pair<Double, Double>>): Pair<Double, Double> {
        val learningRate = .0003
        var guess = Pair(0.0, 0.0)
        for (i in 1..10000000) {
            guess = updateGuess(guess, learningRate, videoGameData)
            if (i % 1000 == 0) println("Guess: $guess")
            if (i % 1000 == 0) println("Cost: ${cost(videoGameData, guess)}")
        }
        return guess
    }

    class Data(val x: Double, val y: Double)

    @Test
    fun name() {
        val fileContent = Tests::class.java.getResource("/data.json").readText()
        val moshi = Moshi.Builder().build()
        val type = Types.newParameterizedType(List::class.java, Data::class.java)
        val adapter: JsonAdapter<List<Data>> = moshi.adapter(type)
        val data = adapter.fromJson(fileContent)!!.map { Pair(it.x, it.y) }.toTypedArray()
        val learningParameters = findLearningParameters(data)
        println(learningParameters)
    }
}

updateGuess.kt

    fun updateGuess(
        guess: Pair<Double, Double>,
        learningRate: Double,
        videoGameData: Array<Pair<Double, Double>>
    ): Pair<Double, Double> {
        val (m, b)  = guess
        val mGradient = videoGameData.fold(0.0) { acc: Double, pair: Pair<Double, Double> ->
            val (x, y) = pair
            acc + ((((m * x) + b) - y) * x)
        } / videoGameData.size
        val bGradient = videoGameData.fold(0.0) { acc: Double, pair: Pair<Double, Double> ->
            val (x, y) = pair
            acc + ((((m * x) + b) - y))
        } / videoGameData.size
        val newM = m - (learningRate * mGradient)
        val newB = b - (learningRate * bGradient)
        return Pair(newM, newB)
    }