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

Ripal Patel, Khushali Obhaliya, Palak Patel, Anita Bhatt, Bhargav Goradiya


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.


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

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