DOI

The aim of the work is to create matrix of feature objects for machine learning problems. The task is to search for data sources, develop a preprocessing algorithm, process statistical community data and form a matrix of feature objects for its further use in the clustering problem. Methods used: data analysis, finding descriptive statistics, methods of Python libraries: Pandas, NumPy. The novelty of this study lies in solving the problem of searching for relevant data of social network communities and developing an algorithm that forms a matrix of feature objects for its further use by researchers. Result: the analysis of services providing statistics of social networks was carried out, a program code was developed that implements the algorithm for generating a matrix of feature objects. The practical significance lies in the processing relevant statistical data and using a matrix of feature objects in machine learning problems.
Язык оригиналаанглийский
Название основной публикацииData Science and Algorithms in Systems
Подзаголовок основной публикацииProceedings of 6th Computational Methods in Systems and Software 2022
РедакторыR. Silhavy, P. Silhavy, Z. Prokopova
ИздательSpringer Nature
Страницы990-1001
Число страниц12
Том2
ISBN (электронное издание)978-3-031-21438-7
ISBN (печатное издание)9783031214370
DOI
СостояниеОпубликовано - 2023
Событие6th Computational Methods in Systems and Software 2022 - Прага, Чехия
Продолжительность: 13 окт 202215 окт 2022
Номер конференции: 6
https://comesyso.openpublish.eu/

Серия публикаций

НазваниеLNNS
Том597

конференция

конференция6th Computational Methods in Systems and Software 2022
Сокращенное названиеCoMeSySo2022
Страна/TерриторияЧехия
ГородПрага
Период13/10/2215/10/22
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