Prediciting Male Fertility Using Machine Learning Classification Algorithms

Abstract

frequent studies found that, on the way out male fertility around the world in the past years are still declining at a rate of two percent every year. Reasons for this decline range from our higher stressful lifestyles, poor diet, drinking and smoking, or a lack of physical exercises and environmental factors. Some applications of machine learning techniques have been implemented in various fields, majorly in health care. This paper has tested outfit meta arrangement systems, for example, sacking, boosting and stacking for improving the exhibition of the Machine learning calculations. For example, Decision-tree, grouping techniques etc for fundamental quality. The presentation of general AI classifier is contrasted and outfit classifier models and furthermore been confirmed with their precision and mistake rate.

Keywords: Machine Learning, Decision tree, Random forest, Support vector machine, Logistic regression, Classification.