AUCReshaping: improved sensitivity at high-specificity

Abstract The evaluation of deep-learning (DL) systems typically relies on the Area under the Receiver-Operating-Curve (AU-ROC) as a performance metric.However, AU-ROC, in its holistic form, does not sufficiently consider performance within specific ranges of sensitivity and specificity, which are critical for the intended operational context of the

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Credit card fraud detection through machine learning algorithm

Every year, millions of dollars are lost due to fraudulent credit card transactions.To help fraud investigators, more algorithms are turning to powerful machine learning methodologies.Designing fraud detection Shaker algorithms is particularly difficult because to the non-stationary distribution of data, excessively skewed class distributions, and

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Cybersecurity Threats in the Sectors of Oil, Natural Gas and Electric Power in the Context of Technological Evolution

The announcement of the state of global COVID-19 pandemic, in addition to the negative health, economic and social phenomena, has triggered a massive phenomenon of transferring most aspects of human life to Connectors cyberspace.The last decade has shown a geometric progression of the growth of cybersecurity incidents worldwide, including the energ

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Ranking sustainable urban mobility indicators and their matching transport policies to support liveable city Futures: A MICMAC approach

Understanding, promoting and managing sustainable urban mobility better is very critical in the midst of an unprecedented climate crisis.Identifying, evaluating, benchmarking and prioritising its key indicators is a way to ensure that policy-makers Seat Pad Housing will develop those transport strategies and measures necessary to facilitate a more

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