Abstract Knowledge extraction through machine learning techniques has been successfully
applied in a large number of application domains. However, apart from the required …

Automated machine learning (AutoML) aims to automate machine learning (ML) tasks,
eliminating human intervention from the learning process as much as possible. However …

Anomaly-based machine learning-enabled intrusion detection systems (AML-IDSs) show
low performance and prediction accuracy while detecting intrusions in the Internet of Things …

The accurate forecasting of ultra-short-term wind speed is of great significance in theory and
practice. This paper proposes a modes decomposition forecasting approach based on …

An automated system that identifies work at height and the fastening state of safety hooks
using wearable sensors was developed to prevent falls from height (FFH). This system …

Supervised data stream learning depends on the incoming sample's true label to update a
classifier's model. In real life, obtaining the ground truth for each instance is a challenging …

Automated recommendation of machine learning algorithms is receiving a large deal of
attention, not only because they can recommend the most suitable algorithms for a new task …

Meta-learning is increasingly used to support the recommendation of machine learning
algorithms and their configurations. These recommendations are made based on meta-data …

Diabetes mellitus (DM) is a combination of metabolic disorders characterized by elevated
blood glucose levels over a prolonged duration. Undiagnosed DM can give rise to a host of …

With the advancement in pose estimation techniques, human posture detection recently
received considerable attention in many applications, including ergonomics and healthcare …