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This article emphasizes comprehending the “Garbage In, Garbage Out” (GIGO) rationale and ensuring the dataset quality in Machine Learning (ML) applications to achieve high and generalizable performance. An initial step should be added in an ML workflow where researchers evaluate the insights gained by quantitative analysis of the datasets sample and feature spaces. This study contributes towards achieving...
Binary classification is one of the most frequent studies in applied machine learning problems in various domains, from medicine to biology to meteorology to malware analysis. Many researchers use some performance metrics in their classification studies to report their success. However, the literature has shown a widespread confusion about the terminology and ignorance of the fundamental aspects behind...
Application permissions at the core of Android security mechanism are the first leading transparent feature for users to assess any mobile application before download or installation and for experts to analyse any malware. Representing vast, dispersed permissions and achieving clarity is not a trivial matter. In this study, we first examined Android permissions, their groups and formal representations...
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