Internal model

A probability captures the likelihood that something is correct and is normally expressed as a number between 0 (impossible) and 1 (certain). Probabilities are used in machine learning both where a model contains inherent uncertainty and in order to capture the uncertainty of predictions made by imperfect models.

used by
ALG_Averaged one-dependence estimators ALG_Bayesian linear regression ALG_Bayesian network ALG_Discriminant analysis ALG_Markov random field ALG_Naive Bayesian Classifier ALG_Probabilistic latent semantic indexing