Abstract: The K-nearest neighbors (kNNs) algorithm, a cornerstone of supervised learning, relies on similarity measures constrained by real-number-based distance metrics. A critical limitation of ...
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The emergence of using Machine Learning Techniques in software testing started in the 2000s with the rise of Model-Based Testing and early bug prediction models trained on historical defect data. It ...
Abstract: This study proposed an effective machine learning (ML)-based fault diagnosis method for demagnetization faults, including “healthy, 30% unipolar demagnetization, 50% multimagnet ...
The year 2024 is the time when most manual things are being automated with the assistance of Machine Learning algorithms. You’d be surprised at the growing number of ML algorithms that help play chess ...
Banks are important for the development of economies in any financial ecosystem through consumer and business loans. Lending, however, presents risks; thus, banks have to determine the applicant’s ...
1 The Graduate School, ICAR-Indian Agricultural Research Institute, New Delhi, India 2 ICAR-Indian Agricultural Statistics Research Institute, New Delhi, India Early prediction of pest occurrences can ...
Background: With machine learning (ML) carving a niche in diverse medical disciplines, its role in sepsis prediction, a condition where the ‘golden hour’ is critical, is of paramount interest. This ...
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