Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Baiq Siska Febriani Astuti"'
Publikováno v:
Jurnal Informatika, Vol 12, Iss 1, Pp 1-8 (2018)
This study aims to classify bloggers in the Kohkiloye and Boyer Ahmad Province in Iran where causes of users tend cyberspace on there. The database was got from UCI Machine Learning Repository. There are 100th object and 6th variables. All of the var
Externí odkaz:
https://doaj.org/article/a841eb5be62b4d35b5fe0fbcf263305b
Autor:
Wardah Rahmatul Islamiyah, Baiq Siska Febriani Astuti, R. Mohamad Atok, Diah Puspito Wulandari, Anda Iviana Juniani, Santi Wulan Purnami
Publikováno v:
International Journal of Machine Learning and Computing. 11:170-175
EEG signals aids in diagnosing various wave signals recorded by the activities of the brain. It also produces unavoidable artifacts, in the recording process. The purpose of this study therefore is to detect ictal and artefact signals, with the aim o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4ac2ad74670963a6a1165e88a5d28dc5
https://doi.org/10.18178/ijmlc.2021.11.2.1031
https://doi.org/10.18178/ijmlc.2021.11.2.1031
Publikováno v:
Jurnal Informatika, Vol 12, Iss 1, Pp 1-8 (2018)
This study aims to classify bloggers in the Kohkiloye and Boyer Ahmad Province in Iran where causes of users tend cyberspace on there. The database was got from UCI Machine Learning Repository. There are 100th object and 6th variables. All of the var
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ecea87ca20fce1f5c89a3db955560c3d
http://journal.uad.ac.id/index.php/JIFO/article/view/8566
http://journal.uad.ac.id/index.php/JIFO/article/view/8566
Publikováno v:
Inferensi. 1:77
Machine learning is a method or computational algorithm to solve problems based on data that already available from the database. Classification is one of the important methods of supervised learning in machine learning. Support Vector Machine and Lo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d11f2ff6df738214ca87ca2a0acfb619
https://doi.org/10.12962/j27213862.v1i2.6728
https://doi.org/10.12962/j27213862.v1i2.6728