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Two Enhancement Levels for Male Fertility Rate Categorization Using Whale Optimization and Pegasos Algorithms
Abstract
Recently, diseases and health problems that were common only in the elderly became common also among the youth. Some of these medical problems causes include behavioral, environmental, and lifestyle factors. The decrease in fertility rates especially among the male population is one of those problems. Now, machine learning and artificial intelligence algorithms are emerging methodologies as computer-aided decision systems in medical diagnosis and health problems. In this chapter, the incorporation of the bio-inspired whale optimization algorithm (WOA) and Pegasos algorithm are used to enhance the male fertility rate categorization in two levels. Results show that implementing WOA as the second level of enhancement gives better accuracy than the first level of enhancement in Pegasos algorithm with a prediction accuracy value of 90%. Using two machine learning algorithms to categorize the male fertility rate helped in the overall improvement of the proposed system performance to give results that exceeded all recent research results for fertility data.
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