A survey of ensemble learning: Concepts, algorithms, applications, and prospects
Ensemble learning techniques have achieved state-of-the-art performance in diverse
machine learning applications by combining the predictions from two or more base models …
machine learning applications by combining the predictions from two or more base models …
COVID-19 diagnosis: A review of rapid antigen, RT-PCR and artificial intelligence methods
As of 27 December 2021, SARS-CoV-2 has infected over 278 million persons and caused
5.3 million deaths. Since the outbreak of COVID-19, different methods, from medical to …
5.3 million deaths. Since the outbreak of COVID-19, different methods, from medical to …
A neural network ensemble with feature engineering for improved credit card fraud detection
Recent advancements in electronic commerce and communication systems have
significantly increased the use of credit cards for both online and regular transactions …
significantly increased the use of credit cards for both online and regular transactions …
Improved heart disease prediction using particle swarm optimization based stacked sparse autoencoder
Heart disease is the leading cause of death globally. The most common type of heart
disease is coronary heart disease, which occurs when there is a build-up of plaque inside …
disease is coronary heart disease, which occurs when there is a build-up of plaque inside …
A machine learning method with filter-based feature selection for improved prediction of chronic kidney disease
SA Ebiaredoh-Mienye, TG Swart, E Esenogho… - Bioengineering, 2022 - mdpi.com
The high prevalence of chronic kidney disease (CKD) is a significant public health concern
globally. The condition has a high mortality rate, especially in developing countries. CKD …
globally. The condition has a high mortality rate, especially in developing countries. CKD …
Machine learning (ML) techniques to predict breast cancer in imbalanced datasets: a systematic review
A Ghavidel, P Pazos - Journal of Cancer Survivorship, 2023 - Springer
Abstract Knowledge discovery in databases (KDD) is crucial in analyzing data to extract
valuable insights. In medical outcome prediction, KDD is increasingly applied, particularly in …
valuable insights. In medical outcome prediction, KDD is increasingly applied, particularly in …
A deep learning ensemble with data resampling for credit card fraud detection
Credit cards play an essential role in today's digital economy, and their usage has recently
grown tremendously, accompanied by a corresponding increase in credit card fraud …
grown tremendously, accompanied by a corresponding increase in credit card fraud …
An interpretable machine learning approach for hepatitis b diagnosis
Hepatitis B is a potentially deadly liver infection caused by the hepatitis B virus. It is a serious
public health problem globally. Substantial efforts have been made to apply machine …
public health problem globally. Substantial efforts have been made to apply machine …
[HTML][HTML] New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning
Abstract Peer-to-peer (P2P) Lending is a type of financial innovation that offers loans without
intermediaries to individuals and companies. In the P2P lending system, there is a risk of …
intermediaries to individuals and companies. In the P2P lending system, there is a risk of …
[HTML][HTML] Predicting severely imbalanced data disk drive failures with machine learning models
J Ahmed, RC Green II - Machine Learning with Applications, 2022 - Elsevier
Datasets related to hard drive failure, particularly BackBlaze Hard Drive Data, have been
widely studied in the literature using many statistical, machine learning, and deep learning …
widely studied in the literature using many statistical, machine learning, and deep learning …