A review of feature selection methods for machine learning-based disease risk prediction
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 …
complex datasets. One of the promising applications of machine learning is in precision …
A review of feature selection and its methods
Nowadays, being in digital era the data generated by various applications are increasing
drastically both row-wise and column wise; this creates a bottleneck for analytics and also …
drastically both row-wise and column wise; this creates a bottleneck for analytics and also …
A fast hybrid feature selection based on correlation-guided clustering and particle swarm optimization for high-dimensional data
XF Song, Y Zhang, DW Gong… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The “curse of dimensionality” and the high computational cost have still limited the
application of the evolutionary algorithm in high-dimensional feature selection (FS) …
application of the evolutionary algorithm in high-dimensional feature selection (FS) …
[HTML][HTML] Benchmark for filter methods for feature selection in high-dimensional classification data
Feature selection is one of the most fundamental problems in machine learning and has
drawn increasing attention due to high-dimensional data sets emerging from different fields …
drawn increasing attention due to high-dimensional data sets emerging from different fields …
Feature selection in machine learning: A new perspective
High-dimensional data analysis is a challenge for researchers and engineers in the fields of
machine learning and data mining. Feature selection provides an effective way to solve this …
machine learning and data mining. Feature selection provides an effective way to solve this …
Physical principles of brain–computer interfaces and their applications for rehabilitation, robotics and control of human brain states
Brain–computer interfaces (BCIs) development is closely related to physics. In this paper, we
review the physical principles of BCIs, and underlying novel approaches for registration …
review the physical principles of BCIs, and underlying novel approaches for registration …
[HTML][HTML] Relief-based feature selection: Introduction and review
Feature selection plays a critical role in biomedical data mining, driven by increasing feature
dimensionality in target problems and growing interest in advanced but computationally …
dimensionality in target problems and growing interest in advanced but computationally …
Advances in computational intelligence of polymer composite materials: machine learning assisted modeling, analysis and design
The superior multi-functional properties of polymer composites have made them an ideal
choice for aerospace, automobile, marine, civil, and many other technologically demanding …
choice for aerospace, automobile, marine, civil, and many other technologically demanding …
Digitalization and new technologies for sustainable business models at the ship–port interface: A bibliometric analysis
Drawing on the business model innovation theory and the resilience theory, the present
study explores existing literature on the capacity of digitalization and new technologies for …
study explores existing literature on the capacity of digitalization and new technologies for …
Variable-size cooperative coevolutionary particle swarm optimization for feature selection on high-dimensional data
Evolutionary feature selection (FS) methods face the challenge of “curse of dimensionality”
when dealing with high-dimensional data. Focusing on this challenge, this article studies a …
when dealing with high-dimensional data. Focusing on this challenge, this article studies a …