A review of the modification strategies of the nature inspired algorithms for feature selection problem
This survey is an effort to provide a research repository and a useful reference for
researchers to guide them when planning to develop new Nature-inspired Algorithms …
researchers to guide them when planning to develop new Nature-inspired Algorithms …
Disease diagnosis in smart healthcare: Innovation, technologies and applications
KT Chui, W Alhalabi, SSH Pang, PO Pablos, RW Liu… - Sustainability, 2017 - mdpi.com
To promote sustainable development, the smart city implies a global vision that merges
artificial intelligence, big data, decision making, information and communication technology …
artificial intelligence, big data, decision making, information and communication technology …
Enhanced whale optimization algorithm for medical feature selection: A COVID-19 case study
The whale optimization algorithm (WOA) is a prominent problem solver which is broadly
applied to solve NP-hard problems such as feature selection. However, it and most of its …
applied to solve NP-hard problems such as feature selection. However, it and most of its …
Review of swarm intelligence-based feature selection methods
In the past decades, the rapid growth of computer and database technologies has led to the
rapid growth of large-scale datasets. On the other hand, data mining applications with high …
rapid growth of large-scale datasets. On the other hand, data mining applications with high …
Dispersed foraging slime mould algorithm: Continuous and binary variants for global optimization and wrapper-based feature selection
The slime mould algorithm (SMA) is a logical swarm-based stochastic optimizer that is easy
to understand and has a strong optimization capability. However, the SMA is not suitable for …
to understand and has a strong optimization capability. However, the SMA is not suitable for …
Heart disease identification method using machine learning classification in e-healthcare
Heart disease is one of the complex diseases and globally many people suffered from this
disease. On time and efficient identification of heart disease plays a key role in healthcare …
disease. On time and efficient identification of heart disease plays a key role in healthcare …
Feature selection using bare-bones particle swarm optimization with mutual information
X Song, Y Zhang, D Gong, X Sun - Pattern Recognition, 2021 - Elsevier
Feature selection (FS) is an important data processing method in pattern recognition and
data mining. Due to not considering characteristics of the FS problem itself, traditional …
data mining. Due to not considering characteristics of the FS problem itself, traditional …
A hybrid intelligent system framework for the prediction of heart disease using machine learning algorithms
Heart disease is one of the most critical human diseases in the world and affects human life
very badly. In heart disease, the heart is unable to push the required amount of blood to …
very badly. In heart disease, the heart is unable to push the required amount of blood to …
Variable-size cooperative coevolutionary particle swarm optimization for feature selection on high-dimensional data
XF Song, Y Zhang, YN Guo, XY Sun… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
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 …
A survey on evolutionary computation approaches to feature selection
Feature selection is an important task in data mining and machine learning to reduce the
dimensionality of the data and increase the performance of an algorithm, such as a …
dimensionality of the data and increase the performance of an algorithm, such as a …