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A comprehensive survey on feature selection in the various fields of machine learning
Abstract In Machine Learning (ML), Feature Selection (FS) plays a crucial part in reducing
data's dimensionality and enhancing any proposed framework's performance. However, in …
data's dimensionality and enhancing any proposed framework's performance. However, in …
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 …
Recent advances in Grey Wolf Optimizer, its versions and applications
The Grey Wolf Optimizer (GWO) has emerged as one of the most captivating swarm
intelligence methods, drawing inspiration from the hunting behavior of wolf packs. GWO's …
intelligence methods, drawing inspiration from the hunting behavior of wolf packs. GWO's …
Machine learning models for the identification of prognostic and predictive cancer biomarkers: a systematic review
The identification of biomarkers plays a crucial role in personalized medicine, both in the
clinical and research settings. However, the contrast between predictive and prognostic …
clinical and research settings. However, the contrast between predictive and prognostic …
A multi-objective optimization algorithm for feature selection problems
Feature selection (FS) is a critical step in data mining, and machine learning algorithms play
a crucial role in algorithms performance. It reduces the processing time and accuracy of the …
a crucial role in algorithms performance. It reduces the processing time and accuracy of the …
BAOA: binary arithmetic optimization algorithm with K-nearest neighbor classifier for feature selection
The Arithmetic Optimization Algorithm (AOA) is a recently proposed metaheuristic algorithm
that has been shown to perform well in several benchmark tests. The AOA is a metaheuristic …
that has been shown to perform well in several benchmark tests. The AOA is a metaheuristic …
Breast cancer detection in thermograms using a hybrid of GA and GWO based deep feature selection method
Breast cancer is one of the most common reasons for the premature death of women
worldwide. However, early detection and diagnosis of the same can save many lives …
worldwide. However, early detection and diagnosis of the same can save many lives …
Approaches to multi-objective feature selection: a systematic literature review
Feature selection has gained much consideration from scholars working in the domain of
machine learning and data mining in recent years. Feature selection is a popular problem in …
machine learning and data mining in recent years. Feature selection is a popular problem in …
A novel multi-objective forest optimization algorithm for wrapper feature selection
Feature selection is one of the important techniques of dimensionality reduction in data
preprocessing because datasets generally have redundant and irrelevant features that …
preprocessing because datasets generally have redundant and irrelevant features that …
[HTML][HTML] Feature selection using artificial gorilla troop optimization for biomedical data: A case analysis with COVID-19 data
Feature selection (FS) is commonly thought of as a pre-processing strategy for determining
the best subset of characteristics from a given collection of features. Here, a novel discrete …
the best subset of characteristics from a given collection of features. Here, a novel discrete …