private fun optimizeParameters( gradients : ArrayList<Array<Any>> , learningRate : Double ) {
    val weightGradientsList = ArrayList<DoubleArray>()
    for( gradient in gradients ) {
        weightGradientsList.add( gradient[0] as DoubleArray )
    }
    val weightGradients = MathOps.multidimMean( weightGradientsList.toTypedArray()  ).toDoubleArray()

    val biasGradientsList = ArrayList<Double>()
    for( gradient in gradients ) {
        biasGradientsList.add( gradient[1] as Double )
    }
    val biasGradients = ( biasGradientsList.toTypedArray() ).average()
    this.weights = MathOps.subtract( this.weights , MathOps.multiplyScalar( weightGradients , learningRate ) )
    this.bias = this.bias - ( biasGradients * learningRate )
}