Feature selection has been a significant task for data mining and pattern recognition. It aims
to choose the optimal feature subset with the minimum redundancy and the maximum …

Feature selection aims to gain relevant features for improved classification performance and
remove redundant features for reduced computational cost. How to balance these two …

Predicting the popularity of online article sheds light to many applications such as
recommendation, advertising and information retrieval. However, there are several technical …

In imbalanced learning, most standard classification algorithms usually fail to properly
represent data distribution and provide unfavorable classification performance. More …

In this paper, a new classification approach for detection and classification of complex power
quality disturbances (PQDs) using a three-level multiply connected Bayesian network is …

Missing data in datasets remain as a difficulty in terms of data analysis in various research
fields, especially in the medical field, as it affects the treatment and diagnosis that the patient …

This paper investigates the effect of using Multimodal Optimization (MO) techniques on
solving the Feature Selection (FSel) problem. The FSel problem is a high-dimensional …

Ultrasonography is a valuable diagnosis method for thyroid nodules. Automatically
discriminating benign and malignant nodules in the ultrasound images can provide aided …

This paper proposes an actuator fault detection algorithm for vertical take-off and landing
(VTOL) unmanned aerial vehicle (UAV), based on acceleration signals provided by a high …

Big data has already occupied a lot in the information society. The application of big data to
intelligent agriculture is the core development direction for maximizing the utilization of …