FORF-S: A Novel Classification Technique for Class Imbalance Problem

FORF-S: A Novel Classification Technique for Class Imbalance Problem

In recent years, the class imbalance problem that aims to correctly classify imbalanced data sets and improve the classification performance of minority instances has received attention. Such problem can be roughly described as one of the class(es) termed as minority class(es) contains much smaller...

Full description

Bibliographic Details
Main Authors:	Yulin Jian, Mao Ye, Yan Min, Liang Tian, Guangjun Wang
Format:	Article
Language:	English
Published:	IEEE 2020-01-01
Series:	IEEE Access
Subjects:	Imbalanced data online random forest synthetic minority oversampling technique nearest neighbor
Online Access:	https://ieeexplore.ieee.org/document/9272759/

Similar Items

Sampling Safety Coefficient for Multi-class Imbalance Oversampling Algorithm
by: DONG Minggang, LIU Ming, JING Chao
Published: (2020-10-01)

On Improving the Classification of Imbalanced Data
by: Mathews Lincy Meera, et al.
Published: (2017-03-01)

SOUL: Scala Oversampling and Undersampling Library for imbalance classification
by: Néstor Rodríguez, et al.
Published: (2021-07-01)

Synthetic Minority Oversampling Technique for Optimizing Classification Tasks in Botnet and Intrusion-Detection-System Datasets
by: David Gonzalez-Cuautle, et al.
Published: (2020-01-01)

A Highly Adaptive Oversampling Approach to Address the Issue of Data Imbalance
by: Szilvia Szeghalmy, et al.
Published: (2022-05-01)

Cluster-based oversampling with area extraction from representative points for class imbalance learning
by: Zakarya Farou, et al.
Published: (2024-06-01)

Stop Oversampling for Class Imbalance Learning: A Review
by: Ahmad S. Tarawneh, et al.
Published: (2022-01-01)

Constrained Oversampling: An Oversampling Approach to Reduce Noise Generation in Imbalanced Datasets With Class Overlapping
by: Changhui Liu, et al.
Published: (2022-01-01)

Prediction of arrhythmia after intervention in children with atrial septal defect based on random forest
by: Hongxiao Sun, et al.
Published: (2021-06-01)

The Distance-Based Balancing Ensemble Method for Data With a High Imbalance Ratio
by: Dong Chen, et al.
Published: (2019-01-01)

FAWOS: Fairness-Aware Oversampling Algorithm Based on Distributions of Sensitive Attributes
by: Teresa Salazar, et al.
Published: (2021-01-01)

An Imbalanced Fault Diagnosis Method Based on TFFO and CNN for Rotating Machinery
by: Long Zhang, et al.
Published: (2022-11-01)

Explainable artificial intelligence-driven gestational diabetes mellitus prediction using clinical and laboratory markers
by: Varada Vivek Khanna, et al.
Published: (2024-12-01)

Tomek Link and SMOTE Approaches for Machine Fault Classification with an Imbalanced Dataset
by: Elsie Fezeka Swana, et al.
Published: (2022-04-01)

HS-Gen: a hypersphere-constrained generation mechanism to improve synthetic minority oversampling for imbalanced classification
by: Zuowei He, et al.
Published: (2022-12-01)

Enhancement of hepatitis virus immunoassay outcome predictions in imbalanced routine pathology data by data balancing and feature selection before the application of support vector machines
by: Alice M. Richardson, et al.
Published: (2017-08-01)

Prediction of Extracellular Matrix Proteins by Fusing Multiple Feature Information, Elastic Net, and Random Forest Algorithm
by: Minghui Wang, et al.
Published: (2020-01-01)

Predicting the Cochlear Dead Regions Using a Machine Learning-Based Approach with Oversampling Techniques
by: Young-Soo Chang, et al.
Published: (2021-11-01)

Integrating oversampling and ensemble-based machine learning techniques for an imbalanced dataset in dyslexia screening tests
by: Shahriar Kaisar, et al.
Published: (2022-12-01)

VCOS: A Novel Synergistic Oversampling Algorithm in Binary Imbalance Classification
by: Chunkai Zhang, et al.
Published: (2019-01-01)

A Combined Priori and Purity Gaussian OverSampling Algorithm for Imbalanced Data Classification
by: Liangliang Tao, et al.
Published: (2023-01-01)

Prediction of High Capabilities in the Development of Kindergarten Children
by: Yenny Villuendas-Rey, et al.
Published: (2020-04-01)

Detection of Electricity Theft Behavior Based on Improved Synthetic Minority Oversampling Technique and Random Forest Classifier
by: Zhengwei Qu, et al.
Published: (2020-04-01)

Application of Machine Learning to Predict COVID-19 Spread via an Optimized BPSO Model
by: Eman H. Alkhammash, et al.
Published: (2023-09-01)

Synthetic Minority Oversampling Technique pada Averaged One Dependence Estimators untuk Klasifikasi Credit Scoring
by: Omer Heranova
Published: (2019-12-01)

Improved classification of large imbalanced data sets using rationalized technique: Updated Class Purity Maximization Over_Sampling Technique (UCPMOT)
by: Sachin S. Patil, et al.
Published: (2017-12-01)

Improved Oversampling Algorithm for Imbalanced Data Based on K-Nearest Neighbor and Interpolation Process Optimization
by: Yiheng Chen, et al.
Published: (2024-02-01)

A New Oversampling Method Based on the Classification Contribution Degree
by: Zhenhao Jiang, et al.
Published: (2021-01-01)

COMPARISON OF SMOTE RANDOM FOREST AND SMOTE K-NEAREST NEIGHBORS CLASSIFICATION ANALYSIS ON IMBALANCED DATA
by: Jus Prasetya, et al.
Published: (2023-04-01)

An extension of Synthetic Minority Oversampling Technique based on Kalman filter for imbalanced datasets
by: Thejas G.S., et al.
Published: (2022-06-01)

GLoW SMOTE-D: Oversampling Technique to Improve Prediction Model Performance of Students Failure in Courses
by: Susana Limanto, et al.
Published: (2024-01-01)

Predicting Depression: a comparative study of machine learning approaches based on language usage.
by: Luciana Mariñelarena-Dondena, et al.
Published: (2017-01-01)

Application of Imbalanced Data Classification Quality Metrics as Weighting Methods of the Ensemble Data Stream Classification Algorithms
by: Weronika Wegier, et al.
Published: (2020-07-01)

A Hybrid Classification of Imbalanced Hyperspectral Images Using ADASYN and Enhanced Deep Subsampled Multi-Grained Cascaded Forest
by: Debaleena Datta, et al.
Published: (2022-09-01)

Adaptive neighbor synthetic minority oversampling technique under 1NN outcast handling
by: Wacharasak Siriseriwan, et al.
Published: (2017-10-01)

An Ensemble Oversampling Model for Class Imbalance Problem in Software Defect Prediction
by: Shamsul Huda, et al.
Published: (2018-01-01)

Global Data Distribution Weighted Synthetic Oversampling Technique for Imbalanced Learning
by: Zhenfei Wang, et al.
Published: (2021-01-01)

Hyperspectral Image Classification with Imbalanced Data Based on Semi-Supervised Learning
by: Xiaorou Zheng, et al.
Published: (2022-04-01)

Resampling Imbalanced Network Intrusion Datasets to Identify Rare Attacks
by: Sikha Bagui, et al.
Published: (2023-03-01)

Synthetic Minority Oversampling Technique Based on Adaptive Local Mean Vectors and Improved Differential Evolution
by: Zhiju Zhang, et al.
Published: (2022-01-01)