The Empirical Comparison of Machine Learning Algorithm for the Class Imbalanced Problem in Conformational Epitope Prediction

The Empirical Comparison of Machine Learning Algorithm for the Class Imbalanced Problem in Conformational Epitope Prediction

A conformational epitope is a part of a protein-based vaccine. It is challenging to identify using an experiment. A computational model is developed to support identification. However, the imbalance class is one of the constraints to achieving optimal performance on the conformational epitope B cell...

Full description

Bibliographic Details
Main Authors:	Binti Solihah, Azhari Azhari, Aina Musdholifah
Format:	Article
Language:	Indonesian
Published:	Universitas Muhammadiyah Purwokerto 2021-05-01
Series:	Jurnal Informatika
Subjects:	sampling-based method, class imbalance, conformational epitope, b-cell, machine learning-based
Online Access:	http://jurnalnasional.ump.ac.id/index.php/JUITA/article/view/9969

Similar Items

Clustering-based undersampling with random over sampling examples and support vector machine for imbalanced classification of breast cancer diagnosis
by: Jue Zhang, et al.
Published: (2019-10-01)

Reduced-Kernel Weighted Extreme Learning Machine Using Universum Data in Feature Space (RKWELM-UFS) to Handle Binary Class Imbalanced Dataset Classification
by: Roshani Choudhary, et al.
Published: (2022-02-01)

Feature Selection and Ensemble Learning Techniques in One-Class Classifiers: An Empirical Study of Two-Class Imbalanced Datasets
by: Chih-Fong Tsai, et al.
Published: (2021-01-01)

Hybrid Sampling and Dynamic Weighting-Based Classification Method for Multi-Class Imbalanced Data Stream
by: Meng Han, et al.
Published: (2023-05-01)

The balancing trick: Optimized sampling of imbalanced datasets—A brief survey of the recent State of the Art
by: Dr. Seba Susan, et al.
Published: (2021-04-01)

Addressing Class Overlap under Imbalanced Distribution: An Improved Method and Two Metrics
by: Zhuang Li, et al.
Published: (2021-09-01)

ADASYN-LOF Algorithm for Imbalanced Tornado Samples
by: Zhipeng Qing, et al.
Published: (2022-03-01)

SMOTified-GAN for Class Imbalanced Pattern Classification Problems
by: Anuraganand Sharma, et al.
Published: (2022-01-01)

A Hybrid Sampling Approach for Imbalanced Binary and Multi-Class Data Using Clustering Analysis
by: Abdul Sattar Palli, et al.
Published: (2022-01-01)

SEMA: Antigen B-cell conformational epitope prediction using deep transfer learning
by: Tatiana I. Shashkova, et al.
Published: (2022-09-01)

Grouped SMOTE With Noise Filtering Mechanism for Classifying Imbalanced Data
by: Ke Cheng, et al.
Published: (2019-01-01)

Comprehending B-Cell Epitope Prediction to Develop Vaccines and Immunodiagnostics
by: Salvador Eugenio C. Caoili
Published: (2022-07-01)

An Effective Recursive Technique for Multi-Class Classification and Regression for Imbalanced Data
by: Tahira Alam, et al.
Published: (2019-01-01)

A Novel Domain Adaptation-Based Intelligent Fault Diagnosis Model to Handle Sample Class Imbalanced Problem
by: Zhongwei Zhang, et al.
Published: (2021-05-01)

A Class-Imbalanced Deep Learning Fall Detection Algorithm Using Wearable Sensors
by: Jing Zhang, et al.
Published: (2021-09-01)

Learning From Imbalanced Data Using Triplet Adversarial Samples
by: Jaesub Yun, et al.
Published: (2023-01-01)

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

Conformational epitope matching and prediction based on protein surface spiral features
by: Ying-Tsang Lo, et al.
Published: (2021-05-01)

Hybrid Approach with Distance Feature for Multi-Class Imbalanced Datasets
by: Hartono Hartono, et al.
Published: (2023-02-01)

A Novel Double Ensemble Algorithm for the Classification of Multi-Class Imbalanced Hyperspectral Data
by: Daying Quan, et al.
Published: (2022-08-01)

Hybrid Undersampling and Oversampling for Handling Imbalanced Credit Card Data
by: Maram Alamri, et al.
Published: (2024-01-01)

Two Stage Comparison of Classifier Performances for Highly Imbalanced Datasets
by: Goran Oreški, et al.
Published: (2015-12-01)

An Experimental Investigation of Calibration Techniques for Imbalanced Data
by: Lanlan Huang, et al.
Published: (2020-01-01)

Biased support vector machine and weighted-smote in handling class imbalance problem
by: Hartono Hartono, et al.
Published: (2018-03-01)

Ensemble MultiBoost Based on RIPPER Classifier for Prediction of Imbalanced Software Defect Data
by: Haitao He, et al.
Published: (2019-01-01)

Improving Outcome Prediction for Traumatic Brain Injury From Imbalanced Datasets Using RUSBoosted Trees on Electroencephalography Spectral Power
by: Nor Safira Elaina Mohd Noor, et al.
Published: (2021-01-01)

SOM-US: A Novel Under-Sampling Technique for Handling Class Imbalance Problem
by: Ajay Kumar
Published: (2024-03-01)

The Impact of Partial Balance of Imbalanced Dataset on Classification Performance
by: Qing Li, et al.
Published: (2022-04-01)

A Novel Clustering-Based Three Level Under-Sampling Algorithm for Class Imbalance Problem
by: Vibha Pratap, et al.
Published: (2024-01-01)

Learning from High-Dimensional and Class-Imbalanced Datasets Using Random Forests
by: Barbara Pes
Published: (2021-07-01)

An Investigation on Topic Maps Based Document Classification with Unbalance Classes
by: Maher Baloch, et al.
Published: (2015-07-01)

A Selective Dynamic Sampling Back-Propagation Approach for Handling the Two-Class Imbalance Problem
by: Roberto Alejo, et al.
Published: (2016-07-01)

A New Epitope Selection Method: Application to Design a Multi-Valent Epitope Vaccine Targeting HRAS Oncogene in Squamous Cell Carcinoma
by: Kush Savsani, et al.
Published: (2021-12-01)

In Silico Epitope-Based Vaccine Prediction against Fungal Infection Aspergillosis
by: Anamika Basu
Published: (2022-07-01)

Adjusting Decision Boundary for Class Imbalanced Learning
by: Byungju Kim, et al.
Published: (2020-01-01)

An Empirical Evaluation of Stacked Ensembles With Different Meta-Learners in Imbalanced Classification
by: Seng Zian, et al.
Published: (2021-01-01)

An Experimental Analysis of Drift Detection Methods on Multi-Class Imbalanced Data Streams
by: Abdul Sattar Palli, et al.
Published: (2022-11-01)

Hellinger distance-based stable sparse feature selection for high-dimensional class-imbalanced data
by: Guang-Hui Fu, et al.
Published: (2020-03-01)

A Novel Classification Method for Class-imbalanced Data and Its Application in microRNA Recognition
by: Xia Geng, et al.
Published: (2018-06-01)

Dynamic learning for imbalanced data in learning chest X-ray and CT images
by: Saeed Iqbal, et al.
Published: (2023-06-01)