如何在Python中计算逻辑Sigmoid函数? [英] How to calculate a logistic sigmoid function in Python?

问题描述

这是一个逻辑S型函数:

This is a logistic sigmoid function:

我知道x.我现在如何在Python中计算F(x)?

I know x. How can I calculate F(x) in Python now?

假设x = 0.458.

Let's say x = 0.458.

F(x)=?

推荐答案

这应该做到:

import math

def sigmoid(x):
  return 1 / (1 + math.exp(-x))

现在您可以通过以下方式进行测试:

And now you can test it by calling:

>>> sigmoid(0.458)
0.61253961344091512

更新:请注意，以上内容主要旨在将给定表达式直接一对一转换为Python代码.它没有经过测试，或者在数字上是可靠的实现.如果您知道您需要一个非常可靠的实现，那么我相信其他人实际上已经对此问题进行了一些思考.

Update: Note that the above was mainly intended as a straight one-to-one translation of the given expression into Python code. It is not tested or known to be a numerically sound implementation. If you know you need a very robust implementation, I'm sure there are others where people have actually given this problem some thought.

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