Data mining for processing experimental data in high energy andnuclear physics led to many multiparametric problems, two of them are consid-ered: (i) hypothesis testing and classication approaches based on articial neuralnetworks and boosted decision trees (ii) clustering of large amounts of data byso-called growing neural gas. Some examples from the practice of the Joint In-stitute for Nuclear research are given to show how to prepare data to deal withthose approaches.
@article{143,
title = {Novel approaches of data-mining in experimental physics},
journal = {Tatra Mountains Mathematical Publications},
volume = {51},
year = {2012},
doi = {10.2478/tatra.v51i1.143},
language = {EN},
url = {http://dml.mathdoc.fr/item/143}
}
Ososkov, Gennady Alexeev. Novel approaches of data-mining in experimental physics. Tatra Mountains Mathematical Publications, Tome 51 (2012) . doi : 10.2478/tatra.v51i1.143. http://gdmltest.u-ga.fr/item/143/