Learning Algorithm

A Learning Algorithm is an algorithm of a learning method that can be implemented into a learning system to solve a learning task (to improve task performance on some learning task over multiple algorithm runs).

• AKA: Induction Algorithm, Formal Learning Process, Data-Driven Algorithm, Data-Centric Algorithm.
• Context:
  • Input: a Data Record Set (a set of Examples)
  • output: a Predictive Model.
  • It can formalize an Informal Learning Process.
  • It can range from being an Unsupervised Learning Algorithm to being a Supervised Learning Algorithm.
• Example(s):
  • 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:
    • Neural Network Learning Algorithm.
    • k-Nearest Neighbor Learning Algorithm.
    • Decision Tree Algorithm.
    • Kernel-based Learning Algorithm (such as SVMs).
    • Naive-Bayes Learning Algorithm.
    • Reinforcement Learning Algorithm,
    • Inductive Logic Algorithm.
  • …
• Counter-Example(s):
  • a Deductive Algorithm.
  • an Abductive Algorithm.
• See: Inductive Reasoning, Function Approximation Algorithm, Data Mining Algorithm.

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References

2009

• http://en.wikipedia.org/wiki/Learning
  • 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

2006

• (Mitchell, 2006) ⇒ Tom M. Mitchell. (2006). “The Discipline of Machine Learning." Machine Learning Department technical report CMU-ML-06-108, Carnegie Mellon University.
  • A scientific field is best defined by the central question it studies. The field of Machine Learning seeks to answer the question “How can we build computer systems that automatically improve with experience, and what are the fundamental laws that govern all learning processes?”

1998

• (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.

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