In: Tatra Mountains Mathematical Publications, vol. 51, no. 1
Gennadii A. Ososkov
Detaily:
Rok, strany: 2012, 131 - 140
Kľúčové slová:
data mining, high energy physics, computer experiment, artificial neural network, boosted decision trees, growing neural gas
O článku:
Data mining for processing experimental data in high energy and nuclear physics led to many multiparametric problems, two of them are considered: (i) hypothesis testing and classification approaches based on artificial neural networks and boosted decision trees (ii) clustering of large amounts of data by so-called growing neural gas. Some examples from the practice of the Joint Institute for Nuclear research are given to show how to prepare data to deal with those approaches.
Ako citovať:
ISO 690:
Ososkov, G. 2012. Novel approaches of data-mining in experimental physics. In Tatra Mountains Mathematical Publications, vol. 51, no.1, pp. 131-140. 1210-3195.
APA:
Ososkov, G. (2012). Novel approaches of data-mining in experimental physics. Tatra Mountains Mathematical Publications, 51(1), 131-140. 1210-3195.