80% Confidence Isn’t 80% Certainty: The Truth About Prediction Probabilities

In machine learning, a predicted probability of 80% doesn’t equate to an 80% chance of an event happening. Instead, it indicates the model’s confidence level that an instance belongs to the positive class. For example, if a model predicts an 80% probability, it means the model is 80% confident in its classification, not that there’s an 80% real-world likelihood of the event. This distinction is crucial for interpreting and using these probabilities in practical decision-making. Understanding and calibrating these probabilities can significantly enhance the reliability of machine learning models in various applications.

Source: towardsdatascience.com

Related Videos

How to systematically approach truth – Bayes' rule

Uncertainty Quantification (1): Enter Conformal Predictors

Bayes' Theorem EXPLAINED with Examples

Techniques in Uncertainty Reasoning and Certainty Factors

"Decision Making under Model Uncertainty" Richard Bradley (LSE)

A Tutorial on Conformal Prediction