Samara University Repository
Welcome to the Samara University repository!
This is an open electronic archive created to preserve and disseminate the scientific results of our university. The works of researchers, faculty members, and students are available to everyone for academic and research purposes.
The repository contains dissertations, research articles, educational and methodological materials, monographs, and regulatory documents. The collections cover a wide range of fields: from aerospace technologies, engine engineering, and computer science to history, linguistics, mathematics, and ecology. The archive brings together the scientific heritage of the university, including materials prepared during the period of Samara State Aerospace University and Samara State University.
Looking for publications by author, title, date, or subject? Full-text search will provide relevant results. Want to explore the academic life more closely? Browse materials by the universityâs organizational units.
Descriptions of all publications and articles available in the repository can be found in the libraryâs electronic catalog. Staff and students can log in via the menu "Login -> My Resource Archive" using their personal account credentials (SSAU_id).
Use the archive for study, research, and professional development!
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Ситникова, Н.В. | |
| dc.contributor.author | Парингер, Р.А. | |
| dc.contributor.author | Куприянов, А.В. | |
| dc.date | 2016 | |
| dc.date.accessioned | 2025-08-22T12:19:48Z | - |
| dc.date.available | 2025-08-22T12:19:48Z | - |
| dc.date.issued | 2016 | |
| dc.identifier.identifier | Dspace\SGAU\20161219\60924 | |
| dc.identifier.citation | Материалы Международной конференции и молодёжной школы «Информационные технологии и нанотехнологии», с. 1096-1099 | |
| dc.identifier.isbn | 978-5-7883-1078-7 | |
| dc.identifier.uri | http://repo.ssau.ru/jspui/handle/123456789/11534 | - |
| dc.description.abstract | Приводится краткий обзор двух методов классификации: метод ближайшего соседа и случайный лес. Оба метода реализованы с помощью технологии MapReduce, с целью применения к большим объемам данных. Приводится сравнительный анализ результатов, полученных на тестовых данных Heterogeneity Activity Recognition Data Set из репозитория UCI. | |
| dc.language | rus | |
| dc.publisher | Издательство СГАУ | |
| dc.title | Сравнительное исследование алгоритмов классификации больших объемов данных | |
| dc.type | Article | |
| local.identifier.olduri | http://repo.ssau.ru/handle/Informacionnye-tehnologii-i-nanotehnologii/Sravnitelnoe-issledovanie-algoritmov-klassifikacii-bolshih-obemov-dannyh-60924 | |
| local.identifier.olduri | http://repo.ssau.ru/handle/Informacionnye-tehnologii-i-nanotehnologii/Sravnitelnoe-issledovanie-algoritmov-klassifikacii-bolshih-obemov-dannyh-60924 | |
| Appears in Collections: | Информационные технологии и нанотехнологии | |
| File | Description | Size | Format | |
|---|---|---|---|---|
| 1096-1099.pdf | Основная статья | 289.01 kB | Adobe PDF | View/Open |
Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.