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http://elartu.tntu.edu.ua/handle/lib/24469
| Title: | Выкарыстанне бібліятэкі scikit-learn ў задачы класіфікацыі рухаў трэкбола |
| Other Titles: | Використання бібліотеки scikit-learn в завданні класифікації рухів трекбола Using scikit-learn library classification problem of trackball movements |
| Authors: | Пархац, К. Г. |
| Affiliation: | Брэсцкі дзяржаўны тэхнічны універсітэт, konstantinparhoc@gmail.com |
| Bibliographic description (Ukraine): | Пархац К. Г. Выкарыстанне бібліятэкі scikit-learn ў задачы класіфікацыі рухаў трэкбола / Пархац К. Г. // FOSS Lviv 2017, 27-30 квітня 2017 року. — Львів : Т.Б. Сорока, 2017. — С. 71–73. |
| Bibliographic description (International): | Parkhats K. H. (2017) Vykorystannia biblioteky scikit-learn v zavdanni klasyfikatsii rukhiv trekbola. FOSS Lviv 2017 (Lviv, 27-30 April 2017), pp. 71-73 [in Belarusian]. |
| Is part of: | Матеріали сьомої науково-практичної конференції FOSS Lviv 2017, 2017 Proceedings of Free/Libre and Open-Source Software Lviv-2017, 2017 |
| Conference/Event: | Сьома науково-практична конференція FOSS Lviv 2017 |
| Journal/Collection: | Матеріали сьомої науково-практичної конференції FOSS Lviv 2017 |
| Issue Date: | 27-Apr-2017 |
| Date of entry: | 1-Apr-2018 |
| Publisher: | Т.Б. Сорока |
| Place of the edition/event: | Львів Lviv |
| Temporal Coverage: | 27-30 квітня 2017 року 27-30 April 2017 |
| Number of pages: | 3 |
| Page range: | 71-73 |
| Start page: | 71 |
| End page: | 73 |
| Abstract: | A scikit-learn machine learning library is discussed in conjunction with its usage in the task of a trackball-specific gesture recognition. Specific of the library and its place in the row of open source machine learning tools is covered. Details of the trackball movement recognition solved with use of the support vector machines approach are presented as far as keynotes for the chosen method. |
| URI: | http://elartu.tntu.edu.ua/handle/lib/24469 |
| ISBN: | 978-966-2598-86-5 |
| URL for reference material: | https://youtu.be/6Ec0AhQ5BaM http://www.infoworld.com/article/2853707/robotics/11-open-source-tools-machine-learning.html http://scikit-learn.org/stable/ |
| References (Ukraine): | 1. Yegulalp S. 11 open source tools to make the most of machine learning // InfoWorld, Dec 4, 2014. http://www.infoworld.com/article/2853707/robotics/11-open-source-tools-machine-learning.html 2. Scikit-learn: machine learning in Python. http://scikit-learn.org/stable/ 3. Pedregosa F. et al. Scikit-learn: machine learning in Python // Journal of Machine Learning Research, № 12, 2011. – P. 2825–2830. |
| References (International): | 1. Yegulalp S. 11 open source tools to make the most of machine learning, InfoWorld, Dec 4, 2014. http://www.infoworld.com/article/2853707/robotics/11-open-source-tools-machine-learning.html 2. Scikit-learn: machine learning in Python. http://scikit-learn.org/stable/ 3. Pedregosa F. et al. Scikit-learn: machine learning in Python, Journal of Machine Learning Research, No 12, 2011, P. 2825–2830. |
| Content type: | Conference Abstract |
| Appears in Collections: | FOSS Lviv 2017 |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| FOSSLviv_2017_Parkhats_K_H-Using_scikit_learn_library_71-73.pdf | 297,96 kB | Adobe PDF | View/Open | |
| FOSSLviv_2017_Parkhats_K_H-Using_scikit_learn_library_71-73.djvu | 92,61 kB | DjVu | View/Open | |
| FOSSLviv_2017_Parkhats_K_H-Using_scikit_learn_library_71-73__COVER.png | 1 MB | image/png | View/Open |
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