[HTML][HTML] Variable selection for Naïve Bayes classification
Abstract The Naïve Bayes has proven to be a tractable and efficient method for classification
in multivariate analysis. However, features are usually correlated, a fact that violates the …
in multivariate analysis. However, features are usually correlated, a fact that violates the …
Learning DenseNet features from EEG based spectrograms for subject independent emotion recognition
Subject-independent emotion recognition (SIER) using electroencephalogram (EEG)
signals has always been a challenge among the biomedical research community. One of the …
signals has always been a challenge among the biomedical research community. One of the …
Cost-sensitive probabilistic predictions for support vector machines
Support vector machines (SVMs) are widely used and constitute one of the best examined
and used machine learning models for two-class classification. Classification in SVM is …
and used machine learning models for two-class classification. Classification in SVM is …
Linear cost-sensitive max-margin embedded feature selection for SVM
KY Aram, SS Lam, MT Khasawneh - Expert Systems with Applications, 2022 - Elsevier
The information needed for a certain machine application can be often obtained from a
subset of the available features. Strongly relevant features should be retained to achieve …
subset of the available features. Strongly relevant features should be retained to achieve …
Cost-sensitive feature selection for support vector machines
Feature Selection is a crucial procedure in Data Science tasks such as Classification, since
it identifies the relevant variables, making thus the classification procedures more …
it identifies the relevant variables, making thus the classification procedures more …
Optimal arrangements of hyperplanes for SVM-based multiclass classification
In this paper, we present a novel SVM-based approach to construct multiclass classifiers by
means of arrangements of hyperplanes. We propose different mixed integer (linear and non …
means of arrangements of hyperplanes. We propose different mixed integer (linear and non …
[HTML][HTML] On sparse ensemble methods: An application to short-term predictions of the evolution of COVID-19
Since the seminal paper by Bates and Granger in 1969, a vast number of ensemble
methods that combine different base regressors to generate a unique one have been …
methods that combine different base regressors to generate a unique one have been …
Integration of aggressive bound tightening and Mixed Integer Programming for Cost-sensitive feature selection in medical diagnosis
M Abdulla, MT Khasawneh - Expert Systems with Applications, 2022 - Elsevier
Silent diseases is an umbrella term that captures a spectrum of chronic illnesses that
produce no clinically obvious signs and are diagnosed at advanced stages when the …
produce no clinically obvious signs and are diagnosed at advanced stages when the …
Constrained Naïve Bayes with application to unbalanced data classification
Abstract The Naïve Bayes is a tractable and efficient approach for statistical classification. In
general classification problems, the consequences of misclassifications may be rather …
general classification problems, the consequences of misclassifications may be rather …
Classification of Critical Stages of Damage by Support Vector Machine
NB Shaik, K Jongkittinarukorn - 2024 International Conference …, 2024 - ieeexplore.ieee.org
It is essential for estimating the failure of metallic components and to classify the faults on a
real-time basis in process monitoring for the better product quality of a metal specimen; so …
real-time basis in process monitoring for the better product quality of a metal specimen; so …