Results 101 to 110 of about 103,585 (306)

A comprehensive survey on imbalanced data learning

Frontiers of Computer Science
Abstract With the expansion of data availability, machine learning (ML) has achieved remarkable breakthroughs in both academia and industry. However, imbalanced data distributions are prevalent in various types of raw data and severely hinder the performance of ML by biasing the decision-making processes.
Xinyi Gao 0001, Dongting Xie, Yihang Zhang, Zhengren Wang, Chong Chen 0001, Conghui He, Hongzhi Yin, Wentao Zhang 0001   +7 more
openaire   +4 more sources

Enhancing classification performance over noise and imbalanced data problems

, 2012
This research presents the development of techniques to handle two issues in data classification: noise and imbalanced data problems. Noise is a significant problem that can degrade the quality of training data in any learning algorithm.
Jeatrakul, Piyasak
core  

Cyclic azapeptide CD36 ligand attenuates cardiac injury and reduces long‐chain fatty acid accumulation after myocardial ischemia–reperfusion in mice

FEBS Open Bio, EarlyView.
In a murine model of myocardial ischemia and reperfusion (MI/R), the CD36 azapeptide ligand MPE‐298 reduces cardiac injury and transiently lowers left ventricular long‐chain fatty acids (LCFAs) accumulation 3 h after reperfusion, accompanied by a decrease of oxidative stress and inflammation‐associated genes' expression in the heart and adipose tissue.
Jade Gauvin, Naghme Radmannia, David N. Huynh, Liliane Ménard, Caroline Daneault, Maïté Veilleux, Ahsanullah Ahsanullah, André C. Carpentier, William D. Lubell, Matthieu Ruiz, Huy Ong, Sylvie Marleau, Simon‐Pierre Gravel   +12 more
wiley   +1 more source

Class prediction for high-dimensional class-imbalanced data

BMC Bioinformatics, 2010
Background The goal of class prediction studies is to develop rules to accurately predict the class membership of new samples. The rules are derived using the values of the variables available for each subject: the main characteristic of high-dimensional
Lusa Lara, Blagus Rok
doaj   +1 more source

Data for: Tree-Based Space Partition and Merging Ensemble Learning Framework for Imbalanced Problems

, 2019
In the experiment of imbalanced problems, 50 imbalanced data sets from the Knowledge Extraction based on Evolutionary Learning (KEEL: http://www.keel.es/) are used in this paper. Every data set is a 5x3 cell with 5 rows and 3 columns.
Wang, Z (via Mendeley Data)
core   +1 more source

Hyperosmotic stress‐induced redistribution of pre‐mRNA cleavage factor I subunits is associated with shifts in alternative polyadenylation

FEBS Open Bio, EarlyView.
Hyperosmotic stress triggers the relocation of the CFIm complex from the nucleus to the cytoplasm. This shift creates a nuclear ‘stoichiometric bottleneck’, limiting CFIm availability for mRNA processing. Consequently, specific mRNAs like NUDT21 and DICER1 undergo targeted 3′UTR shortening, demonstrating how spatial protein dynamics drive rapid ...
Hitomi Soumiya, Masatake Osawa, Hidefumi Fukumitsu   +2 more
wiley   +1 more source

Aging Is a Key Driver for Adult Acute Myeloid Leukemia

Aging and Cancer, EarlyView.
Acute myeloid leukemia (AML) is a classical age‐related hematologic malignancy, and a key driver of AML is aging, which profoundly regulates intrinsic factors such as genomic instability, epigenetic reprogramming, and metabolic dysregulation, and alters bone marrow microenvironment.
Rong Yin, Haojian Zhang
wiley   +1 more source

CUS-RF-Based Credit Card Fraud Detection with Imbalanced Data

Journal of Risk Analysis and Crisis Response (JRACR), 2022
With the continuous expansion of the banks' credit card businesses, credit card fraud has become a serious threat to banking financial institutions. So, the automatic and real-time credit card fraud detection is the meaningful research work.
Wei Li, Cheng-shu Wu, Su-mei Ruan
doaj   +1 more source

Super‐Refractory Status Epilepticus (SRSE) in a Patient With Compound Heterozygous OPA1 Variants: Case Report and Literature Review

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Super‐Refractory Status Epilepticus (SRSE) is a rare, life‐threatening neurological emergency with unclear etiology in many cases. Mitochondrial dysfunction, often due to disease‐causing genetic variants, is increasingly recognized as a cause, with each gene producing distinct pathophysiological mechanisms.
Pouria Mohammadi, Lara Basovic, Christopher Michael McGraw   +2 more
wiley   +1 more source

Improvement of Batch Normalization in Imbalanced Data

CoRR, 2019
In this study, we consider classification problems based on neural networks in data-imbalanced environment. Learning from an imbalanced data set is one of the most important and practical problems in the field of machine learning. A weighted loss function based on cost-sensitive approach is a well-known effective method for imbalanced data sets.
Muneki Yasuda, Seishirou Ueno
openaire   +2 more sources