Počet záznamů: 1
Efficient implementation of compositional models for data mining
- 1.
SYSNO ASEP 0497540 Druh ASEP C - Konferenční příspěvek (mezinárodní konf.) Zařazení RIV D - Článek ve sborníku Název Efficient implementation of compositional models for data mining Tvůrce(i) Kratochvíl, Václav (UTIA-B) RID, ORCID
Jiroušek, Radim (UTIA-B) ORCID
Lee, T. R. (TW)Celkový počet autorů 3 Zdroj.dok. Proceedings of the 21st Czech-Japan Seminar od Data Analysis and Decision Making. - Japan : Aoyama Gakuin University, Japan, 2018 / Sung Shao-Chin ; Vlach Milan - ISBN 978-80-7464-932-5 Rozsah stran s. 80-87 Poč.str. 8 s. Forma vydání Tištěná - P Akce The 21st Czech-Japan Seminar on Data Analysis and Decision Making Datum konání 23.11.2018 - 26.11.2018 Místo konání Kamakura Země JP - Japonsko Typ akce WRD Jazyk dok. eng - angličtina Země vyd. JP - Japonsko Klíč. slova data mining ; mutual information ; compositional models ; conditional independence ; probability theory Vědní obor RIV IN - Informatika Obor OECD Automation and control systems CEP GA16-12010S GA ČR - Grantová agentura ČR Institucionální podpora UTIA-B - RVO:67985556 Anotace A compositional model encodes probabilistic relationships among variables of interest. In connection with various statistical techniques, it represents a practical tool for data modeling and data mining. Structure of the model represents (un)conditional independencies among all variables. Relationships of dependent variables are described by low-dimensional probability distributions. Having a compositional model, a data miner can easily apply an intervention on variables of interest, fix values of other variables (conditioning), or to narrow the context of a problem (marginalization). The model learning process can be controlled to avoid overfitting of data.
In this paper, we present a new semi-supervised web application that will enable researchers to design probabilistic (compositional) models (both causal and stochastic). Thanks to the web architecture of the system, the researchers will always have a possibility to influence the data-based model construction process from any place of the world. It is also expected that the application of this methodology to practical problems will open new problems that will be an inspiration for further theoretical research.Pracoviště Ústav teorie informace a automatizace Kontakt Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Rok sběru 2019
Počet záznamů: 1