Sigmoid Function
Definition
A sigmoid function maps numbers over an S-shaped curve onto a limited range of values.
An S-shaped function that maps real values onto a limited range; this often refers to the logistic function.
Simply explained
Large and small inputs are smoothly brought onto a fixed scale instead of growing indefinitely.
Why it matters in practice
The term helps to select, develop, evaluate AI systems in a well-founded manner and realistically assess their technical risks.
Example from business
A binary classifier converts a logit with the logistic function into a value between zero and one.
Limits and pitfalls
- Interpreting output unchecked as calibrated probability or ignoring saturation and vanishing gradients.
Origin & history
Sigmoid functions were widely used in statistics and early neural networks.
Use in mid-sized companies
- Possible application: A binary classifier converts a logit with the logistic function into a value between zero and one.
Frequently asked questions
What does sigmoid function mean?
An S-shaped function that maps real values onto a limited range; this often refers to the logistic function. What mistakes should be avoided? Interpreting output unchecked as calibrated probability or ignoring saturation and vanishing gradients.
Sources
Source checked on 10.10.2026. Editorial application examples are hypothetical; no evidence of real customer results.
Editorially reviewed on: