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A comprehensive survey on recent metaheuristics for feature selection
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 …
preprocessing due to the ever-increasing sizes in actual data. There have been many …
Metaheuristic algorithms on feature selection: A survey of one decade of research (2009-2019)
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 …
dimension of the feature set while maintaining the accuracy of the performance is the main …
Multiclass feature selection with metaheuristic optimization algorithms: a review
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 …
selection is harder to perform since most classifications are binary. The feature selection …
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 …
A survey on swarm intelligence approaches to feature selection in data mining
One of the major problems in Big Data is a large number of features or dimensions, which
causes the issue of “the curse of dimensionality” when applying machine learning …
causes the issue of “the curse of dimensionality” when applying machine learning …
Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Many fields such as data science, data mining suffered from the rapid growth of data volume
and high data dimensionality. The main problems which are faced by these fields include …
and high data dimensionality. The main problems which are faced by these fields include …
Optimal feature selection-based medical image classification using deep learning model in internet of medical things
Internet of Medical Things (IoMT) is the collection of medical devices and related
applications which link the healthcare IT systems through online computer networks. In the …
applications which link the healthcare IT systems through online computer networks. In the …
Designing a feature selection method based on explainable artificial intelligence
Nowadays, artificial intelligence (AI) systems make predictions in numerous high stakes
domains, including credit-risk assessment and medical diagnostics. Consequently, AI …
domains, including credit-risk assessment and medical diagnostics. Consequently, AI …
A new fusion of grey wolf optimizer algorithm with a two-phase mutation for feature selection
Because of their high dimensionality, dealing with large datasets can hinder the data mining
process. Thus, the feature selection is a pre-process mandatory phase for reducing the …
process. Thus, the feature selection is a pre-process mandatory phase for reducing the …
[HTML][HTML] Virtual collection for distributed photovoltaic data: Challenges, methodologies, and applications
In recent years, with the rapid development of distributed photovoltaic systems (DPVS), the
shortage of data monitoring devices and the difficulty of comprehensive coverage of …
shortage of data monitoring devices and the difficulty of comprehensive coverage of …