Skip to content
The Internet Compass

Encyclopedia of Data Science and Machine Learning

Machine Learning Algorithms

Hamed Taherdoost

Published January 20, 2023Read PDF ↗View on arXiv ↗

Abstract

Machine learning (ML) makes logical patterns out of various types of input data including images, texts, numbers, and any other types of data. Data derived from research will be processes through machine learning ‎algorithms and leads to a prediction that is mainly considered as the output of the machine learning ‎algorithm. Machine learning helps to lower the cost of providing products and services, facilitate business processes and increase the quality of serving customers. In this article, the most popular and commonly used learning algorithms have been reviewed and their specific features are discussed to help select the most appropriate algorithm through comparison in different research projects. Finally, challenges of employing machine learning (ML) for business purposes have been discussed. However, there is not just one practical and efficient method to ‎apply to all data sets, and the appropriate algorithm may differ based on various factors in a study.

Sourced from arXiv · Updated September 2, 2026

Thank you to arXiv for use of its open access interoperability.

View original source ↗Spot an error on this page? Let us know →

FAQ

Common questions

What is "Machine Learning Algorithms" about?

Machine learning (ML) makes logical patterns out of various types of input data including images, texts, numbers, and any other types of data. Data derived from research will be processes through machine learning ‎algorithms and leads to a prediction that is mainly considered as

Who wrote this paper?

Hamed Taherdoost

Where can I read the full paper?

The full text is available as a PDF on arXiv (linked above), published January 20, 2023.

Does this paper have a DOI?

Yes: 10.4018/978-1-7998-9220-5.ch054.