Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Abiodun M. Ikotun"'
Autor:
Tehnan I. A. Mohamed, Absalom E. Ezugwu, Jean Vincent Fonou-Dombeu, Abiodun M. Ikotun, Mohanad Mohammed
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-19 (2023)
Abstract Breast cancer is considered one of the significant health challenges and ranks among the most prevalent and dangerous cancer types affecting women globally. Early breast cancer detection and diagnosis are crucial for effective treatment and
Externí odkaz:
https://doaj.org/article/be337eb958634bfb8e11b1cc6fc0792b
Autor:
Abiodun M. Ikotun, Absalom E. Ezugwu
Publikováno v:
Applied Sciences, Vol 12, Iss 24, p 13019 (2022)
Automatic clustering problems require clustering algorithms to automatically estimate the number of clusters in a dataset. However, the classical K-means requires the specification of the required number of clusters a priori. To address this problem,
Externí odkaz:
https://doaj.org/article/cb3b6acc65bf42e59d53cfbbe962a150
Autor:
Abiodun M. Ikotun, Absalom E. Ezugwu
Publikováno v:
Applied Sciences, Vol 12, Iss 23, p 12275 (2022)
Metaheuristic algorithms have been hybridized with the standard K-means to address the latter’s challenges in finding a solution to automatic clustering problems. However, the distance calculations required in the standard K-means phase of the hybr
Externí odkaz:
https://doaj.org/article/037cb6727de14051addfe03739d0cbc2
Publikováno v:
Applied Sciences, Vol 11, Iss 23, p 11246 (2021)
K-means clustering algorithm is a partitional clustering algorithm that has been used widely in many applications for traditional clustering due to its simplicity and low computational complexity. This clustering technique depends on the user specifi
Externí odkaz:
https://doaj.org/article/96831dd5adf544b5a783982dd1f5bb67
Autor:
Abiodun M Ikotun, Absalom E Ezugwu
Publikováno v:
PLoS ONE, Vol 17, Iss 8, p e0272861 (2022)
Kmeans clustering algorithm is an iterative unsupervised learning algorithm that tries to partition the given dataset into k pre-defined distinct non-overlapping clusters where each data point belongs to only one group. However, its performance is af
Externí odkaz:
https://doaj.org/article/53cfb631ba274d248c69c4ed98bf9e42
Publikováno v:
Information Sciences. 622:178-210
The machine learning (ML) paradigm has gained much popularity today. Its algorithmic models are employed in every field, such as natural language processing, pattern recognition, object detection, image recognition, earth observation and many other r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f2261703ca6b70b0e3df7dcd2b24b17a
http://arxiv.org/abs/2304.07542
http://arxiv.org/abs/2304.07542
Autor:
Absalom E. Ezugwu, Abiodun M. Ikotun, Olaide O. Oyelade, Laith Abualigah, Jeffery O. Agushaka, Christopher I. Eke, Andronicus A. Akinyelu
Publikováno v:
Engineering Applications of Artificial Intelligence. 110:104743