Results 111 to 120 of about 46,171 (307)

UkM: A Novel Undersampling Method Using Modified k-Medoids Algorithm

IEEE Access
Learning from imbalanced data remains a persistent challenge in classification tasks, often resulting in biased model performance and poor generalization, particularly for the minority class.
Duygu Selin Turan
doaj   +1 more source

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  

RNA Sequencing Resolves Cryptic Pathogenic Variants in Mitochondrial Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Mitochondrial diseases are the most common inherited metabolic disorders, characterized by pronounced clinical and genetic heterogeneity that complicates molecular diagnosis. Although DNA‐based sequencing approaches have become standard in genetic testing, up to half of patients remain without a definitive diagnosis.
Zhimei Liu, Xin Duan, Fatemeh Peymani, Jia Wang, Chengjia Bao, Chaolong Xu, Ying Zou, Zixuan Zhang, Yunxi Zhang, Tongyue Li, Martin Pavlov, Junling Wang, Minhan Song, Tianyu Song, Xiaodi Han, Mingxi Sun, Danmin Shen, Ruoyu Duan, Huafang Jiang, Manting Xu, Holger Prokisch, Fang Fang   +21 more
wiley   +1 more source

An Overview on the Advancements of Support Vector Machine Models in Healthcare Applications: A Review

Information
Support vector machines (SVMs) are well-known machine learning algorithms for classification and regression applications. In the healthcare domain, they have been used for a variety of tasks including diagnosis, prognosis, and prediction of disease ...
Rosita Guido, Stefania Ferrisi, Danilo Lofaro, Domenico Conforti   +3 more
doaj   +1 more source

Classification of Imbalanced Dataset \ue2 interaction , re-sampling and stacking

, 2020
In fact, an imbalanced dataset is often encountered. It is caused by the skewed distribution of the dataset between classes. If the imbalanced dataset will be used directly as the basis of the classification models, the analysis may get errors or biases.
Chen, Chun-Xiang
core  

Predicting Implantation Outcome from Imbalanced IVF Dataset [PDF]

, 2020
-Predicting implantation outcomes of invitro fertilization (IVF) embryos is critical for the success of the treatment. We have applied Naive Bayes classifier to an original IVF dataset in order to discriminate embryos according to implantation potentials.
Ayse Bener, Asli Uyar, Mustafa Bahceci, H Nadir Ciray   +3 more
core  

Comparative Effectiveness and Safety of Inebilizumab Versus Rituximab in AQP4‐IgG‐Positive NMOSD

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Rituximab (anti‐CD20, RTX) and inebilizumab (anti‐CD19, INE) represent B‐cell‐depleting therapies used for aquaporin‐4 antibody‐positive (AQP4‐IgG+) neuromyelitis optica spectrum disorder (NMOSD); however, direct comparative evidence remains limited.
Jie Lin, Binbin Xue, Dewei Xie, Jia Li, Juyuan Pan, Lanbing Zhu, Qiaowen Tong, Jing Lin, Ruofan Zhu, Xu Zhang, Junhui Xia, Xiang Li   +11 more
wiley   +1 more source

Impact of imbalanced features on large datasets

Frontiers in Big Data
The exponential growth of image and video data motivates the need for practical real-time content-based searching algorithms. Features play a vital role in identifying objects within images. However, feature-based classification faces a challenge due to uneven class instance distribution. Ideally, each class should have an equal number of instances and
Waleed Albattah, Rehan Ullah Khan
openaire   +3 more sources

Recurrent Hypothermia and Autonomic Dysfunction Secondary to Shapiro Syndrome

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT A 44‐year‐old man presented with recurrent hypothermia, diaphoresis and hypertension. Extensive investigation for infectious, inflammatory, metabolic and endocrine aetiologies was negative. MR scan of the brain demonstrated no lesions but revealed callosal dysgenesis, consistent with Shapiro syndrome.
Naveen Kumar, Jeremy Johnson, Susanne Watkins, Eoin Mulroy   +3 more
wiley   +1 more source

Classification Problem in Imbalanced Datasets

, 2020
La classification est une tâche d'exploration de données. Elle vise à extraire des connaissances à partir de grands ensembles de données. Il existe deux types de classification. La première est connue sous le nom de classification complète, et elle est appliquée à des ensembles de données équilibrés. Cependant, lorsqu'elle est appliquée à des ensembles
Aouatef Mahani, Ahmed Riad Baba Ali
openaire   +2 more sources