Feature selection and feature learning in machine learning applications for gas turbines: A review
The progress of machine learning (ML) in the past years has opened up new opportunities
to the field of gas turbine (GT) modelling. However, successful implementation of ML …
to the field of gas turbine (GT) modelling. However, successful implementation of ML …
Review of feature selection approaches based on grouping of features
With the rapid development in technology, large amounts of high-dimensional data have
been generated. This high dimensionality including redundancy and irrelevancy poses a …
been generated. This high dimensionality including redundancy and irrelevancy poses a …
Accurate detection of Covid-19 patients based on Feature Correlated Naïve Bayes (FCNB) classification strategy
The outbreak of Coronavirus (COVID-19) has spread between people around the world at a
rapid rate so that the number of infected people and deaths is increasing quickly every day …
rapid rate so that the number of infected people and deaths is increasing quickly every day …
Feature reduction for imbalanced data classification using similarity-based feature clustering with adaptive weighted k-nearest neighbors
L Sun, J Zhang, W Ding, J Xu - Information Sciences, 2022 - Elsevier
Most existing imbalanced data classification models mainly focus on the classification
performance of majority class samples, and many clustering algorithms need to manually …
performance of majority class samples, and many clustering algorithms need to manually …
Efficient clustering of emails into spam and ham: The foundational study of a comprehensive unsupervised framework
The spread and adoption of spam emails in malicious activities like information and identity
theft, malware propagation, monetary and reputational damage etc. are on the rise with …
theft, malware propagation, monetary and reputational damage etc. are on the rise with …
[HTML][HTML] Heuristic filter feature selection methods for medical datasets
M Alirezanejad, R Enayatifar, H Motameni… - Genomics, 2020 - Elsevier
Gene selection is the process of selecting the optimal feature subset in an arbitrary dataset.
The significance of gene selection is in high dimensional datasets in which the number of …
The significance of gene selection is in high dimensional datasets in which the number of …
A novel embedded system design for the detection and classification of cardiac disorders
Phonocardiogram (PCG) signals hold significant prognostic and diagnostic information
about cardiac health. Numerous PCG or heart sound based automated detection algorithms …
about cardiac health. Numerous PCG or heart sound based automated detection algorithms …
Hybrid modal-machine learning damage identification approach for beam-like structures
Data-driven damage detection methods are widely researched and implemented due to the
availability of advanced sensing and cloud technologies, where machine learning models …
availability of advanced sensing and cloud technologies, where machine learning models …
An unsupervised approach for content-based clustering of emails into spam and ham through multiangular feature formulation
The rapid growth of spam email attacks and the inherent malicious dynamism within those
attacks on a range of social, personal and business activities warrants an intelligent and …
attacks on a range of social, personal and business activities warrants an intelligent and …
An unsupervised gene selection method based on multivariate normalized mutual information of genes
M Rahmanian, EG Mansoori - Chemometrics and Intelligent Laboratory …, 2022 - Elsevier
Gene expression data analysis has always been challenging due to complex and high-
dimensional samples and genes. Generally, the number of samples is much smaller than …
dimensional samples and genes. Generally, the number of samples is much smaller than …