inferencing

Inferencing is the cognitive or logical process of drawing conclusions from evidence, statements, or data. It involves connecting provided information to implications that are not explicitly stated. The term is used across disciplines, including psychology, linguistics, statistics, and artificial intelligence. In some contexts, inferencing refers to the act itself, while the result of that process is called an inference.

Different modes exist: deductive inference derives conclusions guaranteed by premises; inductive inference extends beyond the premises to probable conclusions; abductive inference proposes the best explanation for the available evidence. In probabilistic and statistical contexts, inference often means estimating unknown quantities from data, and expressing uncertainty through probabilities or confidence intervals. Bayesian inference uses Bayes' theorem to update beliefs as new data arrive.

In language processing and everyday reasoning, inferencing also describes readers or listeners deriving implied meanings, such as conclusions about intent, cause, or relationships not stated outright. In computer science, especially AI, inference includes applying a trained model to new inputs to produce predictions or classifications; it contrasts with training, which builds the model.

Limitations include the quality and completeness of evidence, context, and prior assumptions. Inference can be biased or fallible, especially when data are noisy or incomplete. Clear definitions and transparent assumptions help mitigate misinterpretation.