Automatic design of machine learning via evolutionary computation: A survey
Abstract Machine learning (ML), as the most promising paradigm to discover deep
knowledge from data, has been widely applied to practical applications, such as …
knowledge from data, has been widely applied to practical applications, such as …
Feature selection techniques in the context of big data: taxonomy and analysis
HM Abdulwahab, S Ajitha, MAN Saif - Applied Intelligence, 2022 - Springer
Abstract Recent advancements in Information Technology (IT) have engendered the rapid
production of big data, as enormous volumes of data with high dimensional features grow …
production of big data, as enormous volumes of data with high dimensional features grow …
CNN-based transfer learning–BiLSTM network: A novel approach for COVID-19 infection detection
Abstract Coronavirus disease 2019 (COVID-2019), which emerged in Wuhan, China in 2019
and has spread rapidly all over the world since the beginning of 2020, has infected millions …
and has spread rapidly all over the world since the beginning of 2020, has infected millions …
An effective genetic algorithm-based feature selection method for intrusion detection systems
Availability of suitable and validated data is a key issue in multiple domains for
implementing machine learning methods. Higher data dimensionality has adverse effects on …
implementing machine learning methods. Higher data dimensionality has adverse effects on …
[HTML][HTML] Graph-based relevancy-redundancy gene selection method for cancer diagnosis
Nowadays, microarray data processing is one of the most important applications in
molecular biology for cancer diagnosis. A major task in microarray data processing is gene …
molecular biology for cancer diagnosis. A major task in microarray data processing is gene …
[HTML][HTML] Gene selection for microarray data classification via multi-objective graph theoretic-based method
M Rostami, S Forouzandeh, K Berahmand… - Artificial Intelligence in …, 2022 - Elsevier
In recent decades, the improvement of computer technology has increased the growth of
high-dimensional microarray data. Thus, data mining methods for DNA microarray data …
high-dimensional microarray data. Thus, data mining methods for DNA microarray data …
An efficient binary chimp optimization algorithm for feature selection in biomedical data classification
Accurate classification of high-dimensional biomedical data highly depends on the efficient
recognition of the data's main features which can be used to assist diagnose related …
recognition of the data's main features which can be used to assist diagnose related …
A novel community detection based genetic algorithm for feature selection
The feature selection is an essential data preprocessing stage in data mining. The core
principle of feature selection seems to be to pick a subset of possible features by excluding …
principle of feature selection seems to be to pick a subset of possible features by excluding …
BMPA-TVSinV: A Binary Marine Predators Algorithm using time-varying sine and V-shaped transfer functions for wrapper-based feature selection
Z Beheshti - Knowledge-Based Systems, 2022 - Elsevier
The feature selection problem is one of the pre-processing mechanisms to find the optimal
subset of features from a dataset. The search space of the problem will exponentially grow …
subset of features from a dataset. The search space of the problem will exponentially grow …
Accurate detection of COVID-19 patients based on distance biased Naïve Bayes (DBNB) classification strategy
COVID-19, as an infectious disease, has shocked the world and still threatens the lives of
billions of people. Early detection of COVID-19 patients is an important issue for treating and …
billions of people. Early detection of COVID-19 patients is an important issue for treating and …