Breast Cancer Screening Using a Modified Inertial Projective Algorithms for Split Feasibility Problems
Pennipat Nabheerong,
Warissara Kiththiworaphongkich,
Watcharaporn Cholamjiak
Abstract:To detect breast cancer in mammography screening practice, we modify the inertial relaxed CQ algorithm with Mann’s iteration for solving split feasibility problems in real Hilbert spaces to apply in an extreme learning machine as an optimizer. Weak convergence of the proposed algorithm is proved under certain mild conditions. Moreover, we present the advantage of our algorithm by comparing it with existing machine learning methods. The highest performance value of 85.03% accuracy, 82.56% precision, 87.65% reca… Show more
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