An Overview of Supervised Machine Learning Paradigms and their Classifiers

( Vol-10,Issue-3,March 2024 )

Author(s): Njideka Nkemdilim Mbeledogu, Roseline Uzoamaka Paul, Daniel Ugoh, Kaodilichukwu Chidi Mbeledogu

Total View : 153
Downloads : 10
Page No: 24-32
DOI: 10.22161/ijaems.103.4

Keywords:

Artificial intelligence, Machine learning, supervised learning paradigms

Abstract:

Artificial Intelligence (AI) is the theory and development of computer systems capable of performing complex tasks that historically requires human intelligence such as recognizing speech, making decisions and identifying patterns. These tasks cannot be accomplished without the ability of the systems to learn. Machine learning is the ability of machines to learn from their past experiences. Just like humans, when machines learn under supervision, it is termed supervised learning. In this work, an in-depth knowledge on machine learning was expounded. Relevant literatures were reviewed with the aim of presenting the different types of supervised machine learning paradigms, their categories and classifiers.

Received: 30 Jan 2024; Received in revised form: 14 Feb 2024; Accepted: 22 Mar 2024; Available online: 1 Apr 2024

Cite This Article:

Share: