Probabilistic view of categorization
The probabilistic view of how people classify
exemplars into categories assumes that people base
their classification on similarity. The first to attack the
classical view and to launch the probabilistic view was
Wittgenstein (1953).
There are abstractionist (or prototype) versus
exemplar-based theories of category construction
(Barsalou, 1990).
Contributor
© POSbase 2003
Probabilistic view of categorization
The probabilistic viewpoint was successful in developing
measures of similarities that predicted categorization in humans.
Moreover, it had some practical applications, for example in the
classification of mental disorders in the Diagnostic and Statistical
Manual of Mental Disorders.
The 1968 version (DSM-II, American Psychiatric Association)
defined depressive neurosis in the tradition of the classical view
as „an excessive reaction of depression due to an internal conflict
or to an identifiable event such as the loss of a love object or a
cherished possession“ (p. 40).
© POSbase 2003
Probabilistic view of categorization
The DSM-IIIR in 1987 (and the subsequent 1994 edition) defined
the same disorder in more probabilistic terms: A person needed
to have a depressed mood for most of the day more days than
not for at least two years. Moreover, they have at least two of a
list of six additional symptoms, like insomnia, appetite loss,
fatigue, low self esteem every day for at least two weeks.
The only defining feature is depressed mood; three individuals
suffering from depressive neurosis could share just the
depressed mood, but differ in all the other symptoms.
© POSbase 2003
(Source: Kunda, 1999)
Probabilistic view of categorization
Despite successes of the probabilistic view to overcome
some of the limitations of the classical view, which assumed
defining features, it had some difficulties on its own.
 There were problems to define and determine similarity
(e.g., Taylor et al., 1978).
 It did not take relationships between features into
consideration. For example, a bird (1) has a beak, (2)
has wings, and (3) can fly. 2 and 3 are related to each
other, whereas 1 is independent of both.
 It can not explain theory-based categorization.
© POSbase 2003