Interprétation de la probabilité

Définition

Quantifying the probability of an outcome, classification match of an input or confidence in a hypothesis are basic tasks for any machine model to be useful in the real world, let alone to learn and improve itself.

While humans can rely on intuition and their “gut feelings,” artificial intelligence needs a more scientific way to quantify these abstract concepts into functions an algorithm can use and learn from. So for the purposes of machine learning, regardless of the specific method of calculating and interpreting probability that’s employed, all human forms of intuition can be divided into two broad categories : frequentist (physical properties) probability; and Bayesian (Evidentiary) Probability.

Français

interprétation de la probabilité

Anglais

probability interpretation

Source : Wikipeddia (Probability interpretations)

Source : DeepAI.org