• Jul 29, 2019 News!IJMLC Had Implemented Online Submission System, Please Sumbit New Submissions thorough This System Only!   [Click]
  • Jul 16, 2019 News!Good News! All papers from Volume 9, Number 3 have been indexed by Scopus!   [Click]
  • Jul 08, 2019 News!Vol.9, No.4 has been published with online version.   [Click]
Search
General Information
    • ISSN: 2010-3700 (Online)
    • Abbreviated Title: Int. J. Mach. Learn. Comput.
    • Frequency: Bimonthly
    • DOI: 10.18178/IJMLC
    • Editor-in-Chief: Dr. Lin Huang
    • Executive Editor:  Ms. Cherry L. Chen
    • Abstracing/Indexing: Scopus (since 2017), EI (INSPEC, IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
    • E-mail: ijmlc@ejournal.net
Editor-in-chief
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.

IJMLC 2019 Vol.9(3): 248-254 ISSN: 2010-3700
DOI: 10.18178/ijmlc.2019.9.3.794

A Comparative Analysis of Nonlinear Machine Learning Algorithms for Breast Cancer Detection

Ali Al Bataineh
Abstract—Breast cancer is a form of invasive cancer and one of the most common health problems for women that is globally responsible for a large number of deaths. Accurately classifying and categorizing breast cancer subtype is an essential task. Automated techniques based on artificial intelligence can significantly save time and reduce error. In this paper, a performance comparison between five nonlinear machine learning algorithms viz Multilayer Perceptron (MLP), K-Nearest Neighbors (KNN), Classification and Regression Trees (CART), Gaussian Nave Bayes (NB) and Support Vector Machines (SVM) on the Wisconsin Breast Cancer Diagnostic (WBCD) dataset is conducted. The primary objective is to evaluate the performance in classifying data with respect to efficiency and effectiveness of each algorithm in terms of classification test accuracy, precision, and recall.

Index Terms—Artificial intelligence, machine learning, Multilayer Perceptron (MLP), K-Nearest Neighbors (KNN), Classification and Regression Trees (CART), Gaussian Naive Bayes (NB), Support Vector Machines (SVM).

The author is with the Department of Electrical Engineering and Computer Science, University of Toledo, OH 43606 USA (e-mail: ali.albataineh@utoledo.edu).

[PDF]

Cite: Ali Al Bataineh, "A Comparative Analysis of Nonlinear Machine Learning Algorithms for Breast Cancer Detection," International Journal of Machine Learning and Computing vol. 9, no. 3, pp. 248-254, 2019.

Copyright © 2008-2019. International Journal of Machine Learning and Computing. All rights reserved.
E-mail: ijmlc@ejournal.net