Concept learning

This article has multiple issues. Please help improve it or discuss these issues on the talk page. (Learn how and when to remove these template messages) This article may lack focus or may be about more than one topic. Please help improve this article, possibly by splitting the article and/or by introducing a disambiguation page, or discuss this issue on the talk page. (March 2014) This article may be confusing or unclear to readers. Please help clarify the article. There might be a discussion about this on the talk page. (March 2014) (Learn how and when to remove this template message) This article needs attention from an expert in Psychology. See the talk page for details. WikiProject Psychology may be able to help recruit an expert. (May 2011) This article needs additional citations for verification. Please help improve this article by adding citations to reliable sources. Unsourced material may be challenged and removed. Find sources: "Concept learning" – news · newspapers · books · scholar · JSTOR (April 2009) (Learn how and when to remove this template message) (Learn how and when to remove this template message)

Concept learning, also known as category learning, concept attainment, and concept formation, is defined by Bruner, Goodnow, & Austin (1967) as "the search for and listing of attributes that can be used to distinguish exemplars from non exemplars of various categories".^{[This quote needs a citation]} More simply put, concepts are the mental categories that help us classify objects, events, or ideas, building on the understanding that each object, event, or idea has a set of common relevant features. Thus, concept learning is a strategy which requires a learner to compare and contrast groups or categories that contain concept-relevant features with groups or categories that do not contain concept-relevant features.

The concept of concept attainment requires the following 5 categories:

1. the definition of task;
2. the nature of the examples encountered;
3. the nature of validation procedures;
4. the consequences of specific categorizations; and
5. the nature of imposed restrictions.^[1]

In a concept learning task, a human classifies objects by being shown a set of example objects along with their class labels. The learner simplifies what has been observed by condensing it in the form of an example. This simplified version of what has been learned is then applied to future examples. Concept learning may be simple or complex because learning takes place over many areas. When a concept is difficult, it is less likely that the learner will be able to simplify, and therefore will be less likely to learn. Colloquially, the task is known as learning from examples. Most theories of concept learning are based on the storage of exemplars and avoid summarization or overt abstraction of any kind.

In machine learning, this theory can be applied in training computer programs.^[2]

• Concept learning: Inferring a Boolean-valued function from training examples of its input and output.
• A concept is an idea of something formed by combining all its features or attributes which construct the given concept. Every concept has two components:
  • Attributes: features that one must look for to decide whether a data instance is a positive one of the concept.
  • A rule: denotes what conjunction of constraints on the attributes will qualify as a positive instance of the concept.