Probability

Data Type

A probability captures the likelihood that something is correct and is normally expressed as a number between 0 (impossible) and 1 (certain).

It is used when there is a need to quantify uncertainty in measurements or predictions. Probabilities are commonly applied in scenarios such as classification, risk assessment, and decision-making processes. The technique works by assigning a numerical value to the likelihood of an event occurring, allowing models to make informed decisions based on the degree of certainty.

For example, in a classification task, a model might predict that an email is spam with a prediction probability of 0.8, indicating an 80% chance that the email is spam. In risk assessment, probabilities can be used to estimate the likelihood of different outcomes, such as the probability of a loan defaulting.

Probabilities are important because they allow models to deal with uncertainty and make more accurate predictions. They provide a way to capture the uncertainty of predictions made by imperfect models, enabling better decision-making in uncertain environments.

Alias
Related terms
Prediction Probability Soft Labels