Lín, V. (CZ) Dolejší, P. (CZ) Rauch, J. (CZ) Šimůnek, Milan (UIVT-O)
Zdroj.dok.
Neural Network World. - : Ústav informatiky AV ČR, v. v. i.
- ISSN 1210-0552
Roč. 14, - (2004), s. 411-420
Poč.str.
10 s.
Jazyk dok.
eng - angličtina
Země vyd.
CZ - Česká republika
Klíč. slova
data mining ; contingency tables ; GUHA
Vědní obor RIV
BA - Obecná matematika
CEP
LN00B107 GA MŠMT - Ministerstvo školství, mládeže a tělovýchovy
Anotace
KL-Miner [9] is a datamining procedure that, given input data matrix M and a set of parameters, generates patterns of the form RxC/P. Here R and C are categorial attributes corresponding to the columns of M, and P is a Boolean condition defined in terms of the remaining columns of M. The pattern RxC/P means that R and C are strongly correlated on the submatrix of M formed by all the rows of M that satisfy P. In this paper, we mention the motivation that leads to designing of KL-miner, describing our new implementation of COLLAPS and giving application examples that illustrate the main features of KL-Miner.
