def fit[U <: Regressor](X: Data,
                          y: Array[Double],
                          iterations: Int,
                          intercept: Boolean,
                          seed: Int = this.seed,
                          constructor: (Double,
                                        Option[Array[Double]],
                                        Option[Double],
                                        Boolean,
                                        Int) => U): U = {
    // Create local data array if intercept is used
    val _X: Data = if (intercept) addIntercept(X) else X

    val initializer: Random = new Random()
    initializer.setSeed(seed)

    val init: Weights = Array.fill[Double](_X.head.length)(initializer.nextDouble)

    def fitStream(it: Weights): Stream[Weights] = it #:: fitStream(descend(it, _X, y))

    def beta: Weights = fitStream(init).drop(iterations).head

    constructor(alpha, Some(beta), Some(loss(beta, X, y)), intercept, seed)
  }