val model = mkTrainer.setAlpha(0.0).setLambda(0.0)(data)._1

    // The weights should be the same as the one trained by R
    assert(model.weights(0) ~== 0.586983973 relTol 0.01)
    assert(model.weights(1) ~== 0.454630898 relTol 0.01)
    assert(model.weights(2) ~== -0.019639964 relTol 0.01)
    assert(model.weights(3) ~== 0.107017836 relTol 0.01)
    assert(model.weights(4) ~== 0.766095738 relTol 0.01)
    assert(model.weights(5) ~== -0.105508227 relTol 0.01)
    assert(model.weights(6) ~== 0.045365684 relTol 0.01)
    assert(model.weights(7) ~== 0.004523291 relTol 0.01)
    // Intercept
    assert(model.weights(8) ~== 0.667514485 relTol 0.01)