Selecting relevant feature subsets is vital in machine learning, and multiclass feature
selection is harder to perform since most classifications are binary. The feature selection …

The availability of accurate day-ahead electricity price forecasts is pivotal for electricity
market participants. In the context of trade liberalisation and market harmonisation in the …

Rapid data growth presents many challenges for Machine Learning (ML) tasks as it can
include lots of irrelevant, noisy, and redundant features. Thus, it is vital to select the most …

Alzheimer's disease is one of the most common causes of death in today's world. Magnetic
resonance imaging (MRI) provides an efficient and non-invasive approach for diagnosis of …

Background Cancer diagnosis and clinical outcome prediction are among the most
important emerging applications of gene expression microarray technology with several …

Support Vector Machines (SVMs) are among the most important recent developments in
pattern recognition and statistical machine learning. They have found a great range of …

This paper proposes a new computer-aided method for the skin lesion classification
applicable to both melanocytic skin lesions (MSLs) and nonmelanocytic skin lesions …

Vehicle detection based on image analysis has attracted increasing attention in recent years
due to its low cost, flexibility, and potential toward collision avoidance. In particular, vehicle …

Featured Application Detection of skin diseases is one of today's priority tasks worldwide.
Computer-aided diagnosis is a promising tool for prevention (diagnosis). Abstract The …

Acoustic scene classification is the task of identifying the scene from which the audio signal
is recorded. Convolutional neural network (CNN) models are widely adopted with proven …