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Assessing the quality of rules with a new monotonic interestingness measure z

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

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Assessing the quality of rules with a new monotonic interestingness measure z. / Greco, Salvatore; Slowinski, R.; Szczech, I.

Artificial intelligence and soft computing: proceedings of the 9th international conference. ed. / L. Rutkowski; R. Tadeusiewicz; L. Zadeh; J. Zurada. Vol. 5097 5097. ed. Berlin : Springer, 2008. p. 556-565 (Lecture notes in computer science; No. 5097).

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

Harvard

Greco, S, Slowinski, R & Szczech, I 2008, Assessing the quality of rules with a new monotonic interestingness measure z. in L Rutkowski, R Tadeusiewicz, L Zadeh & J Zurada (eds), Artificial intelligence and soft computing: proceedings of the 9th international conference. 5097 edn, vol. 5097, Lecture notes in computer science, no. 5097, Springer, Berlin, pp. 556-565. https://doi.org/10.1007/978-3-540-69731-2_54

APA

Greco, S., Slowinski, R., & Szczech, I. (2008). Assessing the quality of rules with a new monotonic interestingness measure z. In L. Rutkowski, R. Tadeusiewicz, L. Zadeh, & J. Zurada (Eds.), Artificial intelligence and soft computing: proceedings of the 9th international conference (5097 ed., Vol. 5097, pp. 556-565). (Lecture notes in computer science; No. 5097). Springer. https://doi.org/10.1007/978-3-540-69731-2_54

Vancouver

Greco S, Slowinski R, Szczech I. Assessing the quality of rules with a new monotonic interestingness measure z. In Rutkowski L, Tadeusiewicz R, Zadeh L, Zurada J, editors, Artificial intelligence and soft computing: proceedings of the 9th international conference. 5097 ed. Vol. 5097. Berlin: Springer. 2008. p. 556-565. (Lecture notes in computer science; 5097). https://doi.org/10.1007/978-3-540-69731-2_54

Author

Greco, Salvatore ; Slowinski, R. ; Szczech, I. / Assessing the quality of rules with a new monotonic interestingness measure z. Artificial intelligence and soft computing: proceedings of the 9th international conference. editor / L. Rutkowski ; R. Tadeusiewicz ; L. Zadeh ; J. Zurada. Vol. 5097 5097. ed. Berlin : Springer, 2008. pp. 556-565 (Lecture notes in computer science; 5097).

Bibtex

@inbook{95b260431d7d4c77a9be82391a74b56c,
title = "Assessing the quality of rules with a new monotonic interestingness measure z",
abstract = "The development of effective interestingness measures that help in interpretation and evaluation of the discovered knowledge is an active research area in data mining and machine learning. In this paper, we consider a new Bayesian confirmation measure for {"}if..., then...{"} rules proposed in [4]. We analyze this measure, called Z, with respect to valuable property M of monotonic dependency on the number of objects in the dataset satisfying or not the premise or the conclusion of the rule. The obtained results unveil interesting relationship between Z measure and two other simple and commonly used measures of rule support and anti-support, which leads to efficiency gains while searching for the best rules.",
author = "Salvatore Greco and R. Slowinski and I. Szczech",
year = "2008",
doi = "10.1007/978-3-540-69731-2_54",
language = "English",
isbn = "9783540695721",
volume = "5097",
series = "Lecture notes in computer science",
publisher = "Springer",
number = "5097",
pages = "556--565",
editor = "L. Rutkowski and R. Tadeusiewicz and L. Zadeh and J. Zurada",
booktitle = "Artificial intelligence and soft computing: proceedings of the 9th international conference",
edition = "5097",

}

RIS

TY - CHAP

T1 - Assessing the quality of rules with a new monotonic interestingness measure z

AU - Greco, Salvatore

AU - Slowinski, R.

AU - Szczech, I.

PY - 2008

Y1 - 2008

N2 - The development of effective interestingness measures that help in interpretation and evaluation of the discovered knowledge is an active research area in data mining and machine learning. In this paper, we consider a new Bayesian confirmation measure for "if..., then..." rules proposed in [4]. We analyze this measure, called Z, with respect to valuable property M of monotonic dependency on the number of objects in the dataset satisfying or not the premise or the conclusion of the rule. The obtained results unveil interesting relationship between Z measure and two other simple and commonly used measures of rule support and anti-support, which leads to efficiency gains while searching for the best rules.

AB - The development of effective interestingness measures that help in interpretation and evaluation of the discovered knowledge is an active research area in data mining and machine learning. In this paper, we consider a new Bayesian confirmation measure for "if..., then..." rules proposed in [4]. We analyze this measure, called Z, with respect to valuable property M of monotonic dependency on the number of objects in the dataset satisfying or not the premise or the conclusion of the rule. The obtained results unveil interesting relationship between Z measure and two other simple and commonly used measures of rule support and anti-support, which leads to efficiency gains while searching for the best rules.

U2 - 10.1007/978-3-540-69731-2_54

DO - 10.1007/978-3-540-69731-2_54

M3 - Chapter (peer-reviewed)

SN - 9783540695721

VL - 5097

T3 - Lecture notes in computer science

SP - 556

EP - 565

BT - Artificial intelligence and soft computing: proceedings of the 9th international conference

A2 - Rutkowski, L.

A2 - Tadeusiewicz, R.

A2 - Zadeh, L.

A2 - Zurada, J.

PB - Springer

CY - Berlin

ER -

ID: 231059