The use of machine learning (ML) in healthcare raises numerous ethical concerns,
especially as models can amplify existing health inequities. Here, we outline ethical …

Evaluation metric plays a critical role in achieving the optimal classifier during the
classification training. Thus, a selection of suitable evaluation metric is an important key for …

Background To evaluate binary classifications and their confusion matrices, scientific
researchers can employ several statistical rates, accordingly to the goal of the experiment …

A major issue in the classification of class imbalanced datasets involves the determination of
the most suitable performance metrics to be used. In previous work using several examples …

Перед вами один из самых интересных учебников по машинному обучению–разделу
искусственного интеллекта, изучающего методы построения моделей, способных …

With the increasing number of drones, the danger of their illegal use has become relevant.
This has necessitated the creation of automatic drone protection systems. One of the …

The widespread adoption of Android devices and their capability to access significant
private and confidential information have resulted in these devices being targeted by …

Precision-Recall analysis abounds in applications of binary classification where true
negatives do not add value and hence should not affect assessment of the classifier's …

As one of the most comprehensive machine learning texts around, this book does justice to
the field's incredible richness, but without losing sight of the unifying principles. Peter Flach's …

The field of machine learning has matured to the point where many sophisticated learning
approaches can be applied to practical applications. Thus it is of critical importance that …