A systematic review of emerging feature selection optimization methods for optimal text classification: the present state and prospective opportunities
Specialized data preparation techniques, ranging from data cleaning, outlier detection,
missing value imputation, feature selection (FS), amongst others, are procedures required to …
missing value imputation, feature selection (FS), amongst others, are procedures required to …
An analysis of detection and diagnosis of different classes of skin diseases using artificial intelligence-based learning approaches with hyper parameters
In recent years, metaheuristic optimizers have grown in popularity due to their ability to
efficiently optimize complex, high-dimensional problems that are difficult to solve using …
efficiently optimize complex, high-dimensional problems that are difficult to solve using …
Hybrid CNN and XGBoost model tuned by modified arithmetic optimization algorithm for COVID-19 early diagnostics from X-ray images
Develo** countries have had numerous obstacles in diagnosing the COVID-19 worldwide
pandemic since its emergence. One of the most important ways to control the spread of this …
pandemic since its emergence. One of the most important ways to control the spread of this …
Advanced meta-heuristics, convolutional neural networks, and feature selectors for efficient COVID-19 X-ray chest image classification
The chest X-ray is considered a significant clinical utility for basic examination and
diagnosis. The human lung area can be affected by various infections, such as bacteria and …
diagnosis. The human lung area can be affected by various infections, such as bacteria and …
Tuning hyperparameters of machine learning algorithms and deep neural networks using metaheuristics: A bioinformatics study on biomedical and biological cases
S Nematzadeh, F Kiani, M Torkamanian-Afshar… - … biology and chemistry, 2022 - Elsevier
The performance of a model in machine learning problems highly depends on the dataset
and training algorithms. Choosing the right training algorithm can change the tale of a …
and training algorithms. Choosing the right training algorithm can change the tale of a …
Tuning machine learning models using a group search firefly algorithm for credit card fraud detection
Recent advances in online payment technologies combined with the impact of the COVID-
19 global pandemic has led to a significant escalation in the number of online transactions …
19 global pandemic has led to a significant escalation in the number of online transactions …
Multi-objective task scheduling in cloud computing environment by hybridized bat algorithm
Cloud computing represents relatively new paradigm of utilizing remote computing
resources and is becoming increasingly important and popular technology, that supports on …
resources and is becoming increasingly important and popular technology, that supports on …
An Al-Biruni earth radius optimization-based deep convolutional neural network for classifying monkeypox disease
Human skin diseases have become increasingly prevalent in recent decades, with millions
of individuals in developed countries experiencing monkeypox. Such conditions often carry …
of individuals in developed countries experiencing monkeypox. Such conditions often carry …
Hybrid fruit-fly optimization algorithm with k-means for text document clustering
The fast-growing Internet results in massive amounts of text data. Due to the large volume of
the unstructured format of text data, extracting relevant information and its analysis becomes …
the unstructured format of text data, extracting relevant information and its analysis becomes …
Metaheuristic-based hyperparameter tuning for recurrent deep learning: application to the prediction of solar energy generation
As solar energy generation has become more and more important for the economies of
numerous countries in the last couple of decades, it is highly important to build accurate …
numerous countries in the last couple of decades, it is highly important to build accurate …