Machine learning has shown utility in detecting patterns within large, unstructured, and
complex datasets. One of the promising applications of machine learning is in precision …

Feature selection has become an indispensable machine learning process for data
preprocessing due to the ever-increasing sizes in actual data. There have been many …

Conventional damage detection techniques are gradually being replaced by state-of-the-art
smart monitoring and decision-making solutions. Near real-time and online damage …

Feature selection is a critical and prominent task in machine learning. To reduce the
dimension of the feature set while maintaining the accuracy of the performance is the main …

We formally study how ensemble of deep learning models can improve test accuracy, and
how the superior performance of ensemble can be distilled into a single model using …

Ensembles, especially ensembles of decision trees, are one of the most popular and
successful techniques in machine learning. Recently, the number of ensemble-based …

Data‐driven epoch, the development of machine learning (ML) in materials and device
design is an irreversible trend. Its ability and efficiency to handle nonlinear and game …

Mass spectrometry-based proteomic technique has become indispensable in current
exploration of complex and dynamic biological processes. Instrument development has …

Abstract The Vortex Search Algorithm (VSA) is a meta-heuristic algorithm that has been
inspired by the vortex phenomenon proposed by Dogan and Olmez in 2015. Like other meta …

Feature Selection, a critical data preprocessing step in machine learning, is an effective way
in removing irrelevant variables, thus reducing the dimensionality of input features …