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- AKA: Induction Algorithm, Formal Learning Process, Data-Driven Algorithm, Data-Centric Algorithm.
- a Scientific Learning Method, such as: a Randomized Controlled Experiment Design.
- a Statistical Algorithm, such as: a Linear Least-Squares Fit Algorithm.
- a Data Mining Algorithm.
- a Machine Learning Algorithm, such as:
- See: Inductive Reasoning, Function Approximation Algorithm, Data Mining Algorithm.
- Learning is acquiring new knowledge, behaviors, skills, values, preferences or understanding, and may involve synthesizing different types of information. The ability to learn is possessed by humans, animals and some machines. Progress over time tends to follow learning curves.
- Human learning may occur as part of education or personal development. It may be goal-oriented and may be aided by motivation. The study of how learning occurs is part of neuropsychology, educational psychology, learning theory, and pedagogy.
- Learning may occur as a result of habituation or classical conditioning, seen in many animal species, or as a result of more complex activities such as play, seen only in relatively intelligent animals
- (Mitchell, 2006) ⇒ Tom M. Mitchell. (2006). “The Discipline of Machine Learning." Machine Learning Department technical report CMU-ML-06-108, Carnegie Mellon University.
- (Kohavi & Provost, 1998) ⇒ Ron Kohavi, and Foster Provost. (1998). “Glossary of Terms.” In: Machine Leanring 30(2-3).
- Inducer / induction algorithm: An algorithm that takes as input specific instances and produces a model that generalizes beyond these instances.