Prediction of Likelihood of Contraceptive Method among Women using Machine Learning Techniques

Authors

  • Ripal Patel Student, Electronics & Communication Department, BVM Engineering College, Gujarat, India.
  • Khushali Obhaliya Student, Computer Engineering Department, BVM Engineering College, Gujarat, India.
  • Palak Patel Assistant Professor, Electronics & Communication Department, BVM Engineering College, Gujarat, India.
  • Anita Bhatt Student, Electronics Engineering Department, BVM Engineering College, Gujarat, India.
  • Bhargav Goradiya Student, Electronics & Communication Department, BVM Engineering College, Gujarat, India.

DOI:

https://doi.org/10.37591/jomccmn.v6i1.2055

Keywords:

Contraceptive methods, Data mining, Ensemble classifier, Support vector machine

Abstract

This paper presents the various machine learning techniques and early fusion approach for analyzing usage of contraceptive methods among women. The analysis has been done using various nine features that the usage of contraceptive among women is whether low, high or not at all. This paper also evaluates the effect of contraceptive prediction is affected by men, age, and religion. Finally, comparison of classification accuracy has been employed between 22 classifiers and early fusion of features.

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Published

2019-06-13

Issue

Vol. 6 No. 1 (2019)

Section

Research Articles

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