A class of k-modes algorithms for extracting knowledge structures from data.
Behav Res Methods
; 49(4): 1212-1226, 2017 08.
Article
em En
| MEDLINE
| ID: mdl-27573008
ABSTRACT
One of the most crucial issues in knowledge space theory is the construction of the so-called knowledge structures. In the present paper, a new data-driven procedure for large data sets is described, which overcomes some of the drawbacks of the already existing methods. The procedure, called k-states, is an incremental extension of the k-modes algorithm, which generates a sequence of locally optimal knowledge structures of increasing size, among which a "best" model is selected. The performance of k-states is compared to other two procedures in both a simulation study and an empirical application. In the former, k-states displays a better accuracy in reconstructing knowledge structures; in the latter, the structure extracted by k-states obtained a better fit.
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MEDLINE
Assunto principal:
Algoritmos
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Conhecimento
Limite:
Humans
Idioma:
En
Ano de publicação:
2017
Tipo de documento:
Article