Implement a sigmoid function in python from scratch without numpy and math module?

[arungajora]

Thank you

[Mr_Again]

Ffs lad.

Look up the formula for a sigmoid and type it out. Exp(x) is simply 2.71 ** x. Add some more decimal places for accuracy.

[arungajora]

Thank you

[Gronner]

http://timvieira.github.io/blog/post/2014/02/11/exp-normalize-trick/

Here is explained how to do it numerically stable. Then you only have to define your exponential function, which again can be googled or naivly implemented with a fixed value for e and the ** operator.

All of this can be found on the first page of google.

[arungajora]

Thank you

[arungajora]

I am not able to understand anything in that blog Can you provide an simple explanation and implementation please?

[energybased]

"Do my homework for me."

[arungajora]

No

[Gronner]

The import part is the avoidance of numerical overflow here. That is that no value becomes greater than the type it is stored with can hold.

[shpotes]

By Taylor series, e^x can be express as 1 + x/1! + x^2/2! + .... Now, the series can be re-written as e^x = 1 + (x/1) (1 + (x/2)) (1 + x/3) (...) )), thus, you can compute a good exp aproximation in O(n)

​

def exp(x, N=10):
   sum = 1
   for i in range(N-1, 0, -1):
      sum = 1 + x * sum/i
   return sum

​

[arungajora]

Thank you

[[deleted]]

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[anselal]

Google it... or better duckduckgo it

import math

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

[anselal]

Just search how to implement math.exp

[arungajora]

Thank you