A study on metaheuristics approaches for gene selection in microarray data: algorithms, applications and open challenges
In the recent decades, researchers have introduced an abundance of feature selection
methods many of which are studied and analyzed over the high dimensional datasets …
methods many of which are studied and analyzed over the high dimensional datasets …
A novel multi-objective forest optimization algorithm for wrapper feature selection
B Nouri-Moghaddam, M Ghazanfari… - Expert Systems with …, 2021 - Elsevier
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 …
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 …
A survey of multiobjective evolutionary algorithms for data mining: Part I
A Mukhopadhyay, U Maulik… - IEEE Transactions …, 2013 - ieeexplore.ieee.org
The aim of any data mining technique is to build an efficient predictive or descriptive model
of a large amount of data. Applications of evolutionary algorithms have been found to be …
of a large amount of data. Applications of evolutionary algorithms have been found to be …
Multi-objective evolutionary feature selection for online sales forecasting
Sales forecasting uses historical sales figures, in association with products characteristics
and peculiarities, to predict short-term or long-term future performance in a business, and it …
and peculiarities, to predict short-term or long-term future performance in a business, and it …
Multi-objective grey wolf optimizer for improved cervix lesion classification
Cervical cancer is one of the vital and most frequent cancers, but can be cured effectively if
diagnosed in the early stage. This is a novel effort towards effective characterization of cervix …
diagnosed in the early stage. This is a novel effort towards effective characterization of cervix …
A binary multi-objective chimp optimizer with dual archive for feature selection in the healthcare domain
Medical datasets frequently include vast feature sets with numerous features that are related
to one another. As a result, the curse of dimensionality affects learning from a medical …
to one another. As a result, the curse of dimensionality affects learning from a medical …
Grey wolf optimization based parameter selection for support vector machines
S Eswaramoorthy, N Sivakumaran… - … International journal for …, 2016 - dialnet.unirioja.es
Purpose–The purpose of this paper is to tune support vector machine (SVM) classifier using
grey wolf optimizer (GWO). Design/methodology/approach–The schema of the work aims at …
grey wolf optimizer (GWO). Design/methodology/approach–The schema of the work aims at …
[HTML][HTML] A lexicographic cooperative co-evolutionary approach for feature selection
This paper starts with two hypotheses. The first one is that the simultaneous optimization of
the hyperparameters regulating the classifier within a wrapper method, while the best subset …
the hyperparameters regulating the classifier within a wrapper method, while the best subset …
Gene selection for high-dimensional imbalanced biomedical data based on marine predators algorithm and evolutionary population dynamics
KH Almotairi - Arabian Journal for Science and Engineering, 2024 - Springer
Searching for robust and discriminative features is challenging because of the high-
dimensional characteristics of features. Although numerous dimension-reduction …
dimensional characteristics of features. Although numerous dimension-reduction …