On the public citation graph

TSK fuzzy system fusion at sensitivity-ensemble-level for imbalanced data classification

https://doi.org/10.1016/j.inffus.2022.12.014

0 signed · 97 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.

Claim with ORCID

Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.

See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/11538059_91openalex-snapshot

Borderline-SMOTE: A New Over-Sampling Method in Imbalanced Data Sets Learning

inferredcites →https://doi.org/10.1007/s13748-012-0027-5openalex-snapshot

Surrounding neighborhood-based SMOTE for learning from imbalanced data sets

inferredcites →https://doi.org/10.1016/j.asoc.2014.04.001openalex-snapshot

Least learning machine and its experimental studies on regression capability

inferredcites →https://doi.org/10.1016/j.asoc.2019.105580openalex-snapshot

Maximizing diversity by transformed ensemble learning

inferredcites →https://doi.org/10.1016/j.knosys.2013.09.023openalex-snapshot

Repeated double cross-validation for choosing a single solution in evolutionary multi-objective fuzzy classifier design

inferredcites →https://doi.org/10.1016/j.neucom.2014.05.078openalex-snapshot

Weighted ensemble learning of Bayesian network for gene regulatory networks

inferredcites →https://doi.org/10.1016/j.nicl.2022.102979openalex-snapshot

QSMRim-Net: Imbalance-aware learning for identification of chronic active multiple sclerosis lesions on quantitative susceptibility maps

inferredcites →https://doi.org/10.1109/21.229466openalex-snapshot

A bit-serial VLSI architecture for generating moments in real-time

inferredcites →https://doi.org/10.1109/access.2019.2942641openalex-snapshot

Epileptic EEG Signals Recognition Using a Deep View-Reduction TSK Fuzzy System With High Interpretability

inferredcites →https://doi.org/10.1109/icde48307.2020.00078openalex-snapshot

Self-paced Ensemble for Highly Imbalanced Massive Data Classification

inferredcites →https://doi.org/10.1109/icife.2010.5609385openalex-snapshot

Cluster-based majority under-sampling approaches for class imbalance learning

inferredcites →https://doi.org/10.1109/icnsc.2018.8361344openalex-snapshot

An approach to class imbalance problem based on stacking and inverse random under sampling methods

inferredcites →https://doi.org/10.1109/tbme.2018.2873252openalex-snapshot

Multi-Source Ensemble Learning for the Remote Prediction of Parkinson's Disease in the Presence of Source-Wise Missing Data

inferredcites →https://doi.org/10.1109/tcbb.2018.2827029openalex-snapshot

Predicting Hospital Readmission via Cost-Sensitive Deep Learning

inferredcites →https://doi.org/10.1109/tcyb.2014.2330844openalex-snapshot

Multitask TSK Fuzzy System Modeling by Mining Intertask Common Hidden Structure

inferredcites →https://doi.org/10.1109/tcyb.2014.2372060openalex-snapshot

Diversified Sensitivity-Based Undersampling for Imbalance Classification Problems

inferredcites →https://doi.org/10.1109/tcyb.2018.2877663openalex-snapshot

Geometric Structural Ensemble Learning for Imbalanced Problems

inferredcites →https://doi.org/10.1109/tcyb.2020.3016972openalex-snapshot

A Deep-Ensemble-Level-Based Interpretable Takagi–Sugeno–Kang Fuzzy Classifier for Imbalanced Data

inferredcites →https://doi.org/10.1109/tetci.2017.2761915openalex-snapshot

Stacked-Structure-Based Hierarchical Takagi-Sugeno-Kang Fuzzy Classification Through Feature Augmentation

inferredcites →https://doi.org/10.1109/tfuzz.2014.2328014openalex-snapshot

Minimax Probability TSK Fuzzy System Classifier: A More Transparent and Highly Interpretable Classification Model

inferredcites →https://doi.org/10.1109/tfuzz.2016.2598362openalex-snapshot

Fuzzy Integral With Particle Swarm Optimization for a Motor-Imagery-Based Brain–Computer Interface

inferredcites →https://doi.org/10.1109/tfuzz.2016.2604003openalex-snapshot

Deep TSK Fuzzy Classifier With Stacked Generalization and Triplely Concise Interpretability Guarantee for Large Data

inferredcites →https://doi.org/10.1109/tfuzz.2016.2637405openalex-snapshot

Recognition of Epileptic EEG Signals Using a Novel Multiview TSK Fuzzy System

inferredcites →https://doi.org/10.1109/tfuzz.2017.2688423openalex-snapshot

Spatial Filtering for EEG-Based Regression Problems in Brain–Computer Interface (BCI)

inferredcites →https://doi.org/10.1109/tfuzz.2017.2729507openalex-snapshot

Deep Takagi–Sugeno–Kang Fuzzy Classifier With Shared Linguistic Fuzzy Rules

inferredcites →https://doi.org/10.1109/tfuzz.2019.2907497openalex-snapshot

Biologically Plausible Fuzzy-Knowledge-Out and Its Induced Wide Learning of Interpretable TSK Fuzzy Classifiers

inferredcites →https://doi.org/10.1109/tfuzz.2019.2923377openalex-snapshot

Mean Square Stabilization for Sampled-Data T–S Fuzzy Systems With Random Packet Dropout

inferredcites →https://doi.org/10.1109/tkde.2014.2312336openalex-snapshot

A New Strategy of Cost-Free Learning in the Class Imbalance Problem

inferredcites →https://doi.org/10.1109/tnnls.2015.2496330openalex-snapshot

Brain Dynamics in Predicting Driving Fatigue Using a Recurrent Self-Evolving Fuzzy Neural Network

inferredcites →https://doi.org/10.1109/tnnls.2017.2732482openalex-snapshot

Cost-Sensitive Learning of Deep Feature Representations From Imbalanced Data

inferredcites →https://doi.org/10.1109/tnnls.2017.2750679openalex-snapshot

Continuous Dropout.

inferredcites →https://doi.org/10.1109/tnnls.2018.2872974openalex-snapshot

Shared Nearest-Neighbor Quantum Game-Based Attribute Reduction With Hierarchical Coevolutionary Spark and Its Application in Consistent Segmentation of Neonatal Cerebral Cortical Surfaces

inferredcites →https://doi.org/10.1109/tnnls.2019.2944962openalex-snapshot

Bayes Imbalance Impact Index: A Measure of Class Imbalanced Data Set for Classification Problem

inferredcites →https://doi.org/10.1109/tsmc.2016.2577558openalex-snapshot

Realizing Two-View TSK Fuzzy Classification System by Using Collaborative Learning

inferredcites →https://doi.org/10.1186/s12880-021-00731-zopenalex-snapshot

Prenatal prediction of neonatal respiratory morbidity: a radiomics method based on imbalanced few-shot fetal lung ultrasound images

inferredcites →https://doi.org/10.1186/s13058-020-01291-wopenalex-snapshot

A machine learning model that classifies breast cancer pathologic complete response on MRI post-neoadjuvant chemotherapy

inferredcites →https://doi.org/10.1613/jair.953openalex-snapshot

SMOTE: Synthetic Minority Over-sampling Technique

inferredcites →https://doi.org/10.3389/fnins.2020.00496openalex-snapshot

Seizure Classification From EEG Signals Using an Online Selective Transfer TSK Fuzzy Classifier With Joint Distribution Adaption and Manifold Regularization

inferredcites →https://doi.org/10.3390/life12091380openalex-snapshot

Radiomics from Various Tumour Volume Sizes for Prognosis Prediction of Head and Neck Squamous Cell Carcinoma: A Voted Ensemble Machine Learning Approach

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4458712openalex-extracted

inferred← citeshttps://doi.org/10.2139/ssrn.4810018openalex-extracted

A Bagging Algorithm for Imprecise Classification in Cost-Sensitive Scenarios

inferred← citeshttps://doi.org/10.1007/978-981-95-3019-9_51openalex-snapshot

Semi-Supervised Imbalanced Data Classification with Label Propagation and Resampling Strategies

inferred← citeshttps://doi.org/10.1007/s00521-024-09676-0openalex-snapshot

Imbalanced instance selection based on Laplacian matrix decomposition with weighted k-nearest-neighbor graph

inferred← citeshttps://doi.org/10.1007/s10462-025-11357-wopenalex-snapshot

Effectiveness of data resampling and ensemble learning in multiclass imbalance learning

inferred← citeshttps://doi.org/10.1007/s13369-024-09466-9openalex-snapshot

Deep Learning Model-Based Turn-Over Intention Recognition of Array Air Spring Mattress

inferred← citeshttps://doi.org/10.1007/s40815-024-01971-1openalex-snapshot

Data Informed Initialization of Fuzzy Membership Functions

inferred← citeshttps://doi.org/10.1016/j.asoc.2024.112010openalex-snapshot

Three-way decision-based Takagi–Sugeno–Kang fuzzy classifier for partially labeled data

inferred← citeshttps://doi.org/10.1016/j.asoc.2025.113543openalex-snapshot

Imbalanced Broad Learning System with label relaxation and sample weight adaptation

inferred← citeshttps://doi.org/10.1016/j.bspc.2024.106075openalex-snapshot

Prediction of cervical lymph nodes recurrence after radiotherapy for early nasopharyngeal carcinoma via unsupervised diagnostic feature learning and supervised ensemble classifier learning

inferred← citeshttps://doi.org/10.1016/j.bspc.2026.110178openalex-snapshot

MetaScope: A novel hierarchical framework for predicting distant metastasis of nasopharyngeal carcinoma from class-imbalanced PET/CT images

inferred← citeshttps://doi.org/10.1016/j.compag.2026.112139openalex-snapshot

Intelligent decision-making method for optimal maize seeding rate based on synergistic driving of multi-source field information

inferred← citeshttps://doi.org/10.1016/j.engappai.2024.107934openalex-snapshot

An improved generative adversarial network to oversample imbalanced datasets

inferred← citeshttps://doi.org/10.1016/j.engappai.2024.109972openalex-snapshot

Application of deep learning-based multimodal fusion technology in cancer diagnosis: A survey

inferred← citeshttps://doi.org/10.1016/j.eswa.2024.125422openalex-snapshot

Synthetic oversampling with Mahalanobis distance and local information for highly imbalanced class-overlapped data

inferred← citeshttps://doi.org/10.1016/j.eswa.2026.131845openalex-snapshot

KCPIA: Kolmogorov complexity-based positive instance augmentation for class-imbalance problem

inferred← citeshttps://doi.org/10.1016/j.fss.2025.109695openalex-snapshot

Fully & partially-transmitted-rule fusion: A novel hierarchical fuzzy classification with application to nasopharyngeal cancer’s metastasis prediction

inferred← citeshttps://doi.org/10.1016/j.fss.2026.110025openalex-snapshot

Flexible fusion models for improving the early warning of river floodings, based on a generalization of Takagi-Sugeno-Kang inference system

inferred← citeshttps://doi.org/10.1016/j.heliyon.2024.e40091openalex-snapshot

Transforming agri-food value chains in Bangladesh: A practical application of blockchain for traceability and fair pricing

inferred← citeshttps://doi.org/10.1016/j.inffus.2023.101977openalex-snapshot

Takagi-Sugeno-Kang fuzzy system fusion: A survey at hierarchical, wide and stacked levels

inferred← citeshttps://doi.org/10.1016/j.inffus.2023.102067openalex-snapshot

Large-scale data classification based on the integrated fusion of fuzzy learning and graph neural network

inferred← citeshttps://doi.org/10.1016/j.inffus.2025.103483openalex-snapshot

Fuzzy Apriori classifier enhanced by stacking and adversarial knowledge assistance

inferred← citeshttps://doi.org/10.1016/j.inffus.2025.103524openalex-snapshot

Interpretable research of fuzzy methods: A literature survey

inferred← citeshttps://doi.org/10.1016/j.ins.2024.120212openalex-snapshot

Fuzzy inference system with interpretable fuzzy rules: Advancing explainable artificial intelligence for disease diagnosis—A comprehensive review

inferred← citeshttps://doi.org/10.1016/j.ins.2024.120388openalex-snapshot

A two-view deep interpretable TSK fuzzy classifier under mutually teachable classification criterion

inferred← citeshttps://doi.org/10.1016/j.ins.2024.120976openalex-snapshot

A dynamic broad TSK fuzzy classifier based on iterative learning on progressively rebalanced data

inferred← citeshttps://doi.org/10.1016/j.knosys.2023.110831openalex-snapshot

An AUC-maximizing classifier for skewed and partially labeled data with an application in clinical prediction modeling

inferred← citeshttps://doi.org/10.1016/j.knosys.2025.115009openalex-snapshot

Semi-supervised local entropy-decayed oversampling for imbalanced data

inferred← citeshttps://doi.org/10.1016/j.neucom.2026.135049openalex-snapshot

Lagrange stability of Takagi-Sugeno fuzzy phase-change memory-based neural networks with mixed time-varying delays

inferred← citeshttps://doi.org/10.1109/access.2023.3303509openalex-snapshot

CTGAN-MOS: Conditional Generative Adversarial Network Based Minority-Class-Augmented Oversampling Scheme for Imbalanced Problems

inferred← citeshttps://doi.org/10.1109/access.2024.3365544openalex-snapshot

A Unified Approach Addressing Class Imbalance in Magnetic Resonance Image for Deep Learning Models

inferred← citeshttps://doi.org/10.1109/access.2024.3516376openalex-snapshot

A Robust Enhanced Ensemble Learning Method for Breast Cancer Data Diagnosis on Imbalanced Data

inferred← citeshttps://doi.org/10.1109/tai.2024.3424427openalex-snapshot

An Integrated Fusion Framework for Ensemble Learning Leveraging Gradient-Boosting and Fuzzy Rule-Based Models

inferred← citeshttps://doi.org/10.1109/tce.2025.3525536openalex-snapshot

Fused Fuzzy Deep Learning and Information Steganography for Privacy Preservation in Medical Consumer Electronics

inferred← citeshttps://doi.org/10.1109/tdei.2025.3566933openalex-snapshot

Stacking Deep Scalogram Features With the Enhanced GAN for Defect Recognition in Power Transformers With Highly Imbalanced Partial Discharge Signals

inferred← citeshttps://doi.org/10.1109/tfuzz.2024.3442821openalex-snapshot

Deep Reconciled and Self-Paced TSK Fuzzy System Ensemble for Imbalanced Data Classification: Architecture, Interpretability, and Theory

inferred← citeshttps://doi.org/10.1109/tfuzz.2024.3445389openalex-snapshot

Multiview Fully Interpretable TSK Fuzzy Classifier Enhanced by Multiview Accompanying GMMs

inferred← citeshttps://doi.org/10.1109/tfuzz.2025.3543369openalex-snapshot

Adaptive Broad Network With Graph-Fuzzy Embedding for Imbalanced Noise Data

inferred← citeshttps://doi.org/10.1109/tfuzz.2025.3572937openalex-snapshot

A Lightweight TSK Fuzzy Classifier With Quantitative Equivalent Fuzzy Rules via Adaptive Weighting

inferred← citeshttps://doi.org/10.1109/tkde.2024.3419834openalex-snapshot

Solving the Imbalanced Problem by Metric Learning and Oversampling

inferred← citeshttps://doi.org/10.1109/tnnls.2025.3609722openalex-snapshot

Fuzzy Rule-Based Differentiable Representation Learning

inferred← citeshttps://doi.org/10.1109/tsmc.2025.3649534openalex-snapshot

A Cognitively “AND”-Biased Adversarial TSK Fuzzy Classifier: Training and Generalization Analysis

inferred← citeshttps://doi.org/10.1142/s021951942540072xopenalex-snapshot

DEEP KNOWLEDGE-DRIVEN TSK FUZZY CLASSIFIER FOR EEG-BASED EPILEPSY DIAGNOSIS

inferred← citeshttps://doi.org/10.1177/15578666251372198openalex-snapshot

Microbe Drug Association Prediction with Bernoulli Random Forests

inferred← citeshttps://doi.org/10.1186/s13040-024-00397-7openalex-snapshot

Ensemble feature selection and tabular data augmentation with generative adversarial networks to enhance cutaneous melanoma identification and interpretability

inferred← citeshttps://doi.org/10.2139/ssrn.5257773openalex-snapshot

An Innovative Oversampling Approach Using Functional Data Analysis for Imbalanced Classification

inferred← citeshttps://doi.org/10.3389/fninf.2025.1559335openalex-snapshot

Recognition of MI-EEG signals using extended-LSR-based inductive transfer learning

inferred← citeshttps://doi.org/10.3390/en17164195openalex-snapshot

Onboard Neuro-Fuzzy Adaptive Helicopter Turboshaft Engine Automatic Control System

inferred← citeshttps://doi.org/10.3390/math12050782openalex-snapshot

Mathematical Patterns in Fuzzy Logic and Artificial Intelligence for Financial Analysis: A Bibliometric Study

inferred← citeshttps://doi.org/10.7287/peerj-cs.1429v0.1/reviews/1openalex-snapshot

Peer Review #1 of "TbsNet: the importance of thin-branch structures in CNNs (v0.1)"

inferred← citeshttps://doi.org/10.7287/peerj-cs.1429v0.1/reviews/2openalex-snapshot

Peer Review #2 of "TbsNet: the importance of thin-branch structures in CNNs (v0.1)"

inferred← citeshttps://doi.org/10.7287/peerj-cs.1429v0.1/reviews/3openalex-snapshot

Peer Review #3 of "TbsNet: the importance of thin-branch structures in CNNs (v0.1)"

inferred← citeshttps://doi.org/10.7287/peerj-cs.1429v0.2/reviews/1openalex-snapshot

Peer Review #1 of "TbsNet: the importance of thin-branch structures in CNNs (v0.2)"

inferred← citeshttps://doi.org/10.7287/peerj-cs.1429v0.2/reviews/3openalex-snapshot

Peer Review #3 of "TbsNet: the importance of thin-branch structures in CNNs (v0.2)"

inferred← citeshttps://doi.org/10.7287/peerj-cs.1429v0.3/reviews/2openalex-snapshot

Peer Review #2 of "TbsNet: the importance of thin-branch structures in CNNs (v0.3)"

inferred← citeshttps://doi.org/10.7287/peerj-cs.1429v0.3/reviews/3openalex-snapshot

Peer Review #3 of "TbsNet: the importance of thin-branch structures in CNNs (v0.3)"

inferred← citeshttps://doi.org/10.7717/peerj-cs.1418openalex-snapshot

Human-computer interaction based on background knowledge and emotion certainty

inferred← citeshttps://doi.org/10.7717/peerj-cs.1429openalex-snapshot

TbsNet: the importance of thin-branch structures in CNNs

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.