Isolation Forest detects anomalies by isolating observations. It builds binary trees (called iTrees) by recursively ...

The proliferation of open-source and proprietary software has revolutionized development, enabling rapid innovation and ...

This paper explores the optimization of status updates in sensing systems, focusing on misclassification in machine learning (ML) models. Previous research has primarily tackled the impact of ...

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

Recent advancements in radio frequency machine learning (RFML) have demonstrated the use of raw in-phase and quadrature (IQ) samples for multiple spectrum sensing tasks. Yet, deep learning techniques ...

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Regarding reported experimental errors, only a few of the groups provided the values of standard deviation among measurements. For example, Davis et al. (33) gave ±1% reproducibility among duplicates ...

Machine learning is the scientific discipline that focuses on how computers learn from data. 1, 2 It arises at the intersection of statistics, which seeks to learn relationships from data, and ...