Performance Analysis of Machine Learning Algorithms for Big Data Classification: ML and AI-Based Algorithms for Big Data Analysis

Sanjeev Kumar Punia, Manoj Kumar, Thompson Stephan, Ganesh Gopal Deverajan and Rizwan Patan
Additional contact information
Sanjeev Kumar Punia: JIMS Engineering Management Technical Campus, India
Manoj Kumar: School of Computer Science, University of Petroleum and Energy Studies (UPES), Dehradun, India
Thompson Stephan: Department of Computer Science and Engineering, Faculty of Engineering and Technology, M. S. Ramaiah University of Applied Sciences, Bangalore,Noida, India
Ganesh Gopal Deverajan: Galgotias University, India
Rizwan Patan: Velagapudi Ramakrishna Siddhartha Engineering College, India

International Journal of E-Health and Medical Communications (IJEHMC), 2021, vol. 12, issue 4, 60-75

Abstract: In broad, three machine learning classification algorithms are used to discover correlations, hidden patterns, and other useful information from different data sets known as big data. Today, Twitter, Facebook, Instagram, and many other social media networks are used to collect the unstructured data. The conversion of unstructured data into structured data or meaningful information is a very tedious task. The different machine learning classification algorithms are used to convert unstructured data into structured data. In this paper, the authors first collect the unstructured research data from a frequently used social media network (i.e., Twitter) by using a Twitter application program interface (API) stream. Secondly, they implement different machine classification algorithms (supervised, unsupervised, and reinforcement) like decision trees (DT), neural networks (NN), support vector machines (SVM), naive Bayes (NB), linear regression (LR), and k-nearest neighbor (K-NN) from the collected research data set. The comparison of different machine learning classification algorithms is concluded.

Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... /IJEHMC.20210701.oa4 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jehmc0:v:12:y:2021:i:4:p:60-75

Access Statistics for this article

International Journal of E-Health and Medical Communications (IJEHMC) is currently edited by Joel J.P.C. Rodrigues

More articles in International Journal of E-Health and Medical Communications (IJEHMC) from IGI Global
Bibliographic data for series maintained by Journal Editor ().