Results 31 to 40 of about 23,776,838 (246)

Single-Point Crossover and Jellyfish Optimization for Handling Imbalanced Data Classification Problem

IEEE Access, 2022
The imbalanced datasets and their classification has pulled in as a hot research topic over the years. It is used in different fields, for example, security, finance, health, and many others.
Abeer S. Desuky, Yomna M. Elbarawy, Samina Kausar, Asmaa Hekal Omar, Sadiq Hussain   +4 more
doaj   +1 more source

TGT: A Novel Adversarial Guided Oversampling Technique for Handling Imbalanced Datasets

Egyptian Informatics Journal, 2021
With the volume of data increasing exponentially, there is a growing interest in helping people to benefit from their data regardless of its poor quality.
Ayat Mahmoud, Ayman El-Kilany, Farid Ali, Sherif Mazen   +3 more
doaj   +1 more source

Customer profile classification using transactional data [PDF]

, 2011
Customer profiles are by definition made up of factual and transactional data. It is often the case that due to reasons such as high cost of data acquisition and/or protection, only the transactional data are available for data mining operations ...
Edward T. Apeh, Amanda Schierz, Gabrys, Bogdan, Apeh, Edward Tersoo, Schierz, Amanda C., Bogdan Gabrys   +5 more
core   +1 more source

Oversampling Algorithm Oriented to Subdivision of Minority Class in Imbalanced Data Set [PDF]

Jisuanji gongcheng, 2017
The distributions of the minority class samples in the imbalanced data set are discrepant.Traditional oversampling algorithms do not dispose this discrepancy.In order to handle this discrepancy,this paper proposes an oversampling algorithm oriented to ...
GU Ping,YANG Yang
doaj   +1 more source

HCAB-SMOTE: A Hybrid Clustered Affinitive Borderline SMOTE Approach for Imbalanced Data Binary Classification

, 2020
Binary datasets are considered imbalanced when one of their two classes has less than 40% of the total number of the data instances (i.e., minority class).
Ulukok, Mehtap Kose, Elgedawy, Islam, Al Majzoub, Hisham, Akaydin, Oyku   +3 more
core   +1 more source

Reacting Imbalanced Data via Ensemble Learning Techniques [PDF]

IJCI International Journal of Computers and Information
In machine learning, dealing with imbalanced datasets remains a significant challenge. Class imbalance arises when the distribution of instances across classes is uneven, which can occur in both binary and multiclass problems with varying imbalance ...
Fatma Kindeel, Hatem Abdel-Kader, Amgad Elsayed   +2 more
doaj   +1 more source

Association Between Individualized Education for Kidney Replacement Therapy Modality Selection and Peritoneal Dialysis Initiation: A Cross‐Sectional Study

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Introduction Peritoneal dialysis (PD) is an established home‐based kidney replacement therapy (KRT), but its uptake remains low in Japan. We evaluated whether individualized education in a dedicated outpatient clinic was associated with the initiation of PD.
Yasuko Ito, Ryuichi Yoshimura, Takaki Yamauchi, Yuta Funakoshi, Hirotaka Sonoda, Seiji Kobayashi, Hiroyuki Terawaki, Takafumi Ito   +7 more
wiley   +1 more source

Enhancing classification performance over noise and imbalanced data problems [PDF]

, 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  

Processing imbalanced medical data at the data level with assisted-reproduction data as an example

BioData Mining
Objective Data imbalance is a pervasive issue in medical data mining, often leading to biased and unreliable predictive models. This study aims to address the urgent need for effective strategies to mitigate the impact of data imbalance on classification
Junliang Zhu, Shaowei Pu, Jiaji He, Dongchao Su, Weijie Cai, Xueying Xu, Hongbo Liu   +6 more
doaj   +1 more source

Imbalanced data classification using MapReduce and relief

Journal of Information and Telecommunication, 2018
Classification of imbalanced data has been reported to require modification of standard classification algorithms and lately has attracted a lot of attention due to practical applications in industry, banking and finance.
Joanna Jedrzejowicz, Robert Kostrzewski, Jakub Neumann, Magdalena Zakrzewska   +3 more
doaj   +1 more source