Results 121 to 130 of about 103,585 (306)
Imbalanced data classification algorithm [PDF]
, 2022 This article mainly analyzes the characteristics and challenges of inbalanced data, analyzes the research status of imbalanced data integration classification algorithms and combines the actual situation, based on ensemble learning.
Guo, Quang, Geman, O. V.
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Vestibular Patient Journey: Insights From Vestibular Disorders Association (VeDA) Registry
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Vestibular symptoms impose a high burden of disability. Understanding real‐world diagnostic and treatment pathways can identify care gaps and guide interventions. We aimed to characterize symptom profiles, diagnostic trends, provider involvement, and treatment patterns in vestibular disorders.
Ali Rafati +10 more
wiley +1 more source
PhysioDimClassifier—imbalance data classifier model for IoMT-based remote patient monitoring systems
MethodsXRemote patient monitoring systems (RPMS) using the Internet of Medical Things (IoMT) continuously collect and exchange periodic sensor-observations through communication modules.
Sayyed Johar, G.R. Manjula
doaj +1 more source
Resample-Based Ensemble Framework for Drifting Imbalanced Data Streams
IEEE Access, 2019 Machine learning in real-world scenarios is often challenged by concept drift and class imbalance. This paper proposes a Resample-based Ensemble Framework for Drifting Imbalanced Stream (RE-DI).
Hang Zhang +4 more
doaj +1 more source
A Progressive Sampling Method for Dual-Node Imbalanced Learning with Restricted Data Access
Imbalanced learning, characterised by disproportionate class distributions, impedes the effectiveness of learning algorithms, particularly when available data is scarce.
Chen, W., Qiu, Y., Xu, M.
core +1 more source
Clustering of imbalanced high-dimensional media data
, 2018 Media content in large repositories usually exhibits multiple groups of strongly varying sizes. Media of potential interest often form notably smaller groups.
Breiteneder, Christian; orcid: +4 more
core +1 more source
A Systematic Review and Meta‐Analysis of the Recurrence of Autoimmune Encephalitis
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Autoimmune encephalitis (AE) is a disease with a potential for recurrence, and patients receive immunotherapy to prevent it. However, there is no consensus on the duration of immunotherapy. This study aimed to determine the recurrence rate and identify the risk factors for AE to provide guidance on the duration of immunotherapy ...
Shangkai Bai +5 more
wiley +1 more source
, 2018 A very challenging issue in real world data is that in many domains like medicine, finance, marketing, web, telecommunication, management etc., the distribution of data among classes is inherently imbalanced.
Lincy Mathews, Seetha Hari
core +1 more source
Sex Representation in US Stroke Clinical Trials: A Decade of Trends and Challenges
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Stroke remains a major cause of disability and mortality in the US, with significant sex‐based disparities, and females remain underrepresented in stroke clinical trials. We aimed to examine sex representation in US‐based stroke clinical trials, identify trial characteristics associated with higher female enrollment (≥ 50%), and ...
Chaitali Dagli +5 more
wiley +1 more source
Multi-class protein fold classification using a new ensemble machine learning approach.
, 2003 Protein structure classification represents an important process in understanding the associations between sequence and structure as well as possible functional and evolutionary relationships.
Deville, Y, Gilbert, D, Tan, A
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