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Fetal Risk Prediction Using Optimized Genetic Algorithm – Support Vector Machine Based Feature Selection Techniques

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J. Jayashree, J. Vijayashree, and N.Ch.S.N. Iyengar, 2021. Fetal Risk Prediction Using Optimized Genetic Algorithm – Support Vector Machine Based Feature Selection Techniques. United International Journal for Research & Technology (UIJRT), 2(12), pp.108-113.


Improved feature selection methodology for fetal risk data collection defining important features. The aim is to improve the fetal risk prediction rate by using an optimized technique such as GA-SVM for feature selection. Then the selected features are given to various classifiers such as random forest, naïve bayes, multi- layer perceptron and support vector machine for prediction. As a result, the feature selected by optimized feature selection techniques provides higher accuracy, precision and recall when compared to non-optimized techniques.

Keywords: Fetal, optimization, features, prediction.


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