Question

我必须为此模型函数实现最小二乘拟合算法

class MyScreen: UIViewController , RPBroadcastActivityViewControllerDelegate 

  override func viewDidLoad() {
        super.viewDidLoad()
        // Do any additional setup after loading the view, typically from a nib.

        UIScreen.main.addObserver(self, forKeyPath: "captured", options: .new, context: nil)
         }


let broadcastPickerView = RPSystemBroadcastPickerView(frame: CGRect(x:0, y: 0, width: btnRS.frame.width, height: btnRS.frame.height))
    broadcastPickerView.translatesAutoresizingMaskIntoConstraints = false
    if let button = broadcastPickerView.subviews.first as? UIButton {
        button.imageView?.tintColor = UIColor.white

    }


    btnRS.addSubview(broadcastPickerView)
    broadcastPickerView.tintColor = .yellow
    broadcastPickerView.backgroundColor = .clear
    broadcastPickerView.showsMicrophoneButton = true

    btnRS.titleEdgeInsets = UIEdgeInsets(top: 0, left: 0, bottom: 0, right: 0)


}

我发现的方法是定义函数以计算残差并将其传递给scipy.optimize.leastsq或lmfit。但是，当参数是矢量而不是单个值时，我无法使用多维数据。

Y = a_0 * e^(a_1*x_1+a_2*x_2+...+a_n*x_n)

我收到此错误。

ValueError：设置具有序列的数组元素。

您能从这里为我指出正确的做法吗？

Answer 1

我认为类似的事情应该可以完成：

def residual(variables,X,y):
    a_0 = variables[0]
    a = variables[1:]

    return (y - a_0 * np.exp(X.dot(a)))**2

X = np.random.randn(100,5)
y = np.random.randint(low=0,high=2,size=100)
a = np.random.randn(X.shape[1]+1)
a[0] = 1

res = scipy.optimize.leastsq(residual,a,args=(X,y))

致谢

如何在python中为多维数据实现非线性最小二乘法？

1 个答案: