| Formal Concept Analysis |
Article Index for Formal |
Website Links For Formal |
Information AboutFormal Concept Analysis |
| CATEGORIES ABOUT FORMAL CONCEPT ANALYSIS | |
| machine learning | |
| lattice theory | |
| data mining | |
| ontology computer science | |
There's a one-to-one correspondence between natural property clusters and natural object clusters, and a concept is a pair containing both a natural property cluster and its corresponding natural object cluster. Note the strong parallel between "natural" property clusters and Definition s in terms of individually necessary and jointly sufficient conditions, on one hand, and between "natural" object clusters and the Extension s of such definitions, on the other. ...it also gives you a lattice. FORMAL PRESENTATION [[ '''''Given a set of objects O, a set of Attribute s A, and an indication of which objects have which attributes, concept analysis: # finds all the "concepts" in the input dataset, where a concept is defined as an (Oc ⊆ O, Ac ⊆ A) pair such that A) every object in Oc has every attribute in Ac and B) every object in O (''not'' Oc) that has every attribute in Ac is in Oc. # produces a Lattice indicating which concepts are strict subconcepts of which other concepts.''''']] MISC Provided the input objects and input concepts provide a complete description of the world (never true in practice, but perhaps a reasonable approximation), then: # the set of attributes in each concept can be interpreted as a set of singly necessary and jointly sufficient conditions for defining the set of objects in the concept. # if a set of attributes is ''not'' identified as a concept by the algorithm, then those attributes are not singly necessary and jointly sufficient for defining ''any'' non-empty subset of objects in the world. ... SEE ALSO FURTHER READING
|
|
|