<abstract xmlns="http://www.w3.org/1999/xhtml"><p> 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.</p></abstract>

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.

Novel approaches of data-mining in experimental physics

Joint Institute for Nuclear Research Joliot-Courie str. 6 Dubna Moscow region, 141980 RUSSIA

Tatra Mountains Mathematical Publications

{"article-title":"Novel approaches of data-mining in experimental physics"}

Data mining for processing experimental data in high energy and nuclear physics led to many multiparametric problems, two of them are considered: (i)...

Novel approaches of data-mining in experimental physics

Pubblicato online: 13 nov 2012

Pagine: 131 - 140

DOI: https://doi.org/10.2478/v10127-012-0013-0

Parole chiave
data mining, high energy physics, computer experiment, artificial neural network, boosted decision trees, growing neural gas.

This content is open access.

Novel approaches of data-mining in experimental physics

Pubblicato online: 13 nov 2012

Pagine: 131 - 140

DOI: https://doi.org/10.2478/v10127-012-0013-0

Parole chiavedata mining, high energy physics, computer experiment, artificial neural network, boosted decision trees, growing neural gas.

This content is open access.

Parole chiave
data mining, high energy physics, computer experiment, artificial neural network, boosted decision trees, growing neural gas.