Results 91 to 100 of about 224,004 (328)

Ultimate Pólya Gamma Samplers -- Efficient MCMC for possibly imbalanced binary and categorical data [PDF]

, 2020
Gregor Zens, Sylvia Frühwirth‐Schnatter, Helga Wagner   +2 more
openalex   +1 more source

Extending Bagging for Imbalanced Data [PDF]

, 2013
Various modifications of bagging for class imbalanced data are discussed. An experimental comparison of known bagging modifications shows that integrating with undersampling is more powerful than oversampling. We introduce Local-and-Over-All Balanced bagging where probability of sampling an example is tuned according to the class distribution inside ...
Jerzy Błaszczyński, Jerzy Stefanowski, Łukasz Idkowiak   +2 more
openaire   +1 more source

Age‐Related Characteristics of SYT1‐Associated Neurodevelopmental Disorder

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives We describe the clinical manifestations and developmental abilities of individuals with SYT1‐associated neurodevelopmental disorder (Baker‐Gordon syndrome) from infancy to adulthood. We further describe the neuroradiological and electrophysiological characteristics of the condition at different ages, and explore the associations ...
Sam G. Norwitz, Josefine Eck, Joel S. Winston, Kate Baker   +3 more
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

Predicting Epileptogenic Tubers in Patients With Tuberous Sclerosis Complex Using a Fusion Model Integrating Lesion Network Mapping and Machine Learning

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Accurate localization of epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC) is essential but challenging, as these tubers lack distinct pathological or genetic markers to differentiate them from other cortical tubers.
Tinghong Liu, Qi Wang, Suhui Kuang, Dezhi Cao, Ping Ding, Shaohui Zhang, Haihua Wei, Zhirong Wei, Jinshan Xu, Xinyu Huang, Bing Liu, Shuli Liang   +11 more
wiley   +1 more source

Cognitive Status in People With Epilepsy in the Republic of Guinea: A Prospective, Case–Control Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective People with epilepsy (PWE) may experience cognitive deficits but fail to undergo formal evaluation. This study compares cognitive status between PWE and healthy controls in the West African Republic of Guinea. Methods A cross‐sectional, case–control study was conducted in sequential recruitment phases (July 2024–July 2025) at Ignace ...
Maya L. Mastick, Cheick O. Soumah, Malé Doré, Oumar Mara, Desiré Neldje, Fodé A. Cissé, Toure M. Lamine, Aminata Diallo, Seungwon Lee, Siddharth Satish, Alexander J. X. Chen, Alice Liu, Nomin Enkhtsetseg, Farrah J. Mateen, The Guinea Epilepsy Project   +14 more
wiley   +1 more source

Dual generative adversarial networks based on regression and neighbor characteristics.

PLoS ONE
Imbalanced data is a problem in that the number of samples in different categories or target value ranges varies greatly. Data imbalance imposes excellent challenges to machine learning and pattern recognition.
Weinan Jia, Ming Lu, Qing Shen, Chunzhi Tian, Xuyang Zheng   +4 more
doaj   +1 more source

PhysioDimClassifier—imbalance data classifier model for IoMT-based remote patient monitoring systems

MethodsX
Remote 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

A Recapitulation of Imbalanced Data

International Journal of Innovative Technology and Exploring Engineering, 2020
In today’s authentic universe almost all applications are imbalanced. Data imbalance is growing faster than ever before as many systems are interested in extracting knowledge from lake of data. Imbalance issue occurs because required data is very rare and using that rare data if classification is done we may lead to inaccurate result.
Shaheen Layaq*, Dr. B. Manjula
openaire   +1 more source

An Out‐of‐Place Etiology: Recognizing FMR1 Premutation in the Memory Clinic

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT The FMR1 gene premutation (55–200 CGG repeats) is usually associated with a wide range of symptoms and phenotypes within the Fragile X‐tremor/ataxia syndrome (FXTAS), but may also manifest as predominant or isolated cognitive decline. We describe three male patients referred for progressive cognitive impairment and behavioral changes. Standard
Guido Greco, Caterina Motta, Enrica Marchionni, Maria Rosaria D'Apice, Carlangelo Carrese, Giuseppe Novelli, Alessandro Martorana, Chiara Giuseppina Bonomi   +7 more
wiley   +1 more source