Efficient resampling methods for training support vector machines with imbalanced datasets

Efficient resampling methods for training support vector machines with imbalanced datasets

Bibliografiske detaljer
Main Authors:	Batuwita, R, Palade, V
Format:	Conference item
Udgivet:	2010

Lignende værker

Class Imbalance Learning Methods for Support Vector Machines
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Adjusted Geometric−mean: A Novel Performance Measure for Imbalanced Bioinformatics Datasets Learning
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Udgivet: (2012)

FSVM-CIL: Fuzzy Support Vector Machines for Class Imbalance Learning.
af: Batuwita, R, et al.
Udgivet: (2010)

FSVM−CI: Fuzzy Support Vector Machines for Class Imbalance Learning
af: Batuwita, R, et al.
Udgivet: (2010)

Resampling Technique for Imbalanced Class Handling on Educational Dataset
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Resampling imbalanced data for network intrusion detection datasets
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Udgivet: (2021-01-01)

Support vector machine for solving imbalanced dataset problem /
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Predicting Pulsars from Imbalanced Dataset with Hybrid Resampling Approach
af: Ernesto Lee, et al.
Udgivet: (2021-01-01)

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

Support vector machine for solving imbalanced dataset problem [electronic resource] /
af: Ismail Mohd. Khairuddin, 1987-
Udgivet: (2012)

Ensemble classifier and resampling for imbalanced multiclass learning
af: Sainin, Mohd Shamrie, et al.
Udgivet: (2015)

A stacked ensemble approach with resampling techniques for highly effective fraud detection in imbalanced datasets
af: Idongesit E. Eteng, et al.
Udgivet: (2025-02-01)

Highly Imbalanced Classification of Gout Using Data Resampling and Ensemble Method
af: Xiaonan Si, et al.
Udgivet: (2024-03-01)

Predicting defects in imbalanced data using resampling methods: an empirical investigation
af: Ruchika Malhotra, et al.
Udgivet: (2022-04-01)

Effect of data resampling on feature importance in imbalanced blockchain data: comparison studies of resampling techniques
af: Ismail Alarab, et al.
Udgivet: (2022-06-01)

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af: Zorkeflee, Maisarah, et al.
Udgivet: (2015)

Resampling algorithm for imbalanced data based on their neighbor relationship
af: Rui-feng LI, et al.
Udgivet: (2021-06-01)

Improving Sentiment Analysis Performance on Imbalanced Moroccan Dialect Datasets Using Resample and Feature Extraction Techniques
af: Zineb Nassr, et al.
Udgivet: (2025-01-01)

Validation assessments on resampling method in imbalanced binary classification for linear discriminant analysis
af: Jamaluddin, Ahmad Hakiim, et al.
Udgivet: (2021)

Validation assessments on Resampling Method in Imbalanced Binary Classification for Linear Discriminant Analysis
af: Jamaluddin, Ahmad Hakiim, et al.
Udgivet: (2021)

VALIDATION ASSESSMENTS ON RESAMPLING METHOD IN IMBALANCED BINARY CLASSIFICATION FOR LINEAR DISCRIMINANT ANALYSIS
af: Ahmad Hakiim Jamaluddin, et al.
Udgivet: (2020-11-01)

VALIDATION ASSESSMENTS ON RESAMPLING METHOD IN IMBALANCED BINARY CLASSIFICATION FOR LINEAR DISCRIMINANT ANALYSIS
af: Ahmad Jamaluddin, et al.
Udgivet: (2020-10-01)

Resample-Based Ensemble Framework for Drifting Imbalanced Data Streams
af: Hang Zhang, et al.
Udgivet: (2019-01-01)

Selecting the Suitable Resampling Strategy for Imbalanced Data Classification Regarding Dataset Properties. An Approach Based on Association Models
af: Mohamed S. Kraiem, et al.
Udgivet: (2021-09-01)

BALANCED VS IMBALANCED TRAINING DATA: CLASSIFYING RAPIDEYE DATA WITH SUPPORT VECTOR MACHINES
af: M. Ustuner, et al.
Udgivet: (2016-06-01)

ANALYZING THE IMPACT OF RESAMPLING METHOD FOR IMBALANCED DATA TEXT IN INDONESIAN SCIENTIFIC ARTICLES CATEGORIZATION
af: Ariani Indrawati, et al.
Udgivet: (2020-12-01)

CCR: A combined cleaning and resampling algorithm for imbalanced data classification
af: Koziarski Michał, et al.
Udgivet: (2017-12-01)

Comparison of Resampling Techniques for Imbalanced Datasets in Machine Learning: Application to Epileptogenic Zone Localization From Interictal Intracranial EEG Recordings in Patients With Focal Epilepsy
af: Giulia Varotto, et al.
Udgivet: (2021-11-01)

A Novel Ensemble Framework Based on K-Means and Resampling for Imbalanced Data
af: Huajuan Duan, et al.
Udgivet: (2020-03-01)

Deep Learning-Based Imbalanced Classification With Fuzzy Support Vector Machine
af: Ke-Fan Wang, et al.
Udgivet: (2022-01-01)

An improved non−comparative classification method for human microRNA gene prediction
af: Batuwita, R, et al.
Udgivet: (2008)

Knowledge distillation with resampling for imbalanced data classification: Enhancing predictive performance and explainability stability
af: Kazuki Fujiwara
Udgivet: (2024-12-01)

Anomalous Propagation Echo Classification of Imbalanced Radar Data with Support Vector Machine
af: Hansoo Lee, et al.
Udgivet: (2016-01-01)

Increasing Minority Recall Support Vector Machine Model for Imbalanced Data Classification
af: Chunye Wu, et al.
Udgivet: (2021-01-01)

Machine Learning Model for Imbalanced Cholera Dataset in Tanzania
af: Judith Leo, et al.
Udgivet: (2019-01-01)

Robust Rescaled Hinge Loss Twin Support Vector Machine for Imbalanced Noisy Classification
af: Ling-Wei Huang, et al.
Udgivet: (2019-01-01)

Ensemble deep random vector functional link neural net for imbalanced datasets
af: Soo, Jian Xian
Udgivet: (2022)

Determining Resampling Ratios Using BSMOTE and SVM-SMOTE for Identifying Rare Attacks in Imbalanced Cybersecurity Data
af: Sikha S. Bagui, et al.
Udgivet: (2023-10-01)

Using Information on Class Interrelations to Improve Classification of Multiclass Imbalanced Data: A New Resampling Algorithm
af: Janicka Małgorzata, et al.
Udgivet: (2019-12-01)

Improved support vector machine classification for imbalanced medical datasets by novel hybrid sampling combining modified mega-trend-diffusion and bagging extreme learning machine model
af: Liang-Sian Lin, et al.
Udgivet: (2023-09-01)