封面圖片

A neighbourhood undersampling stacked ensemble with H-measure maximising meta-learner for imbalanced classification / Seng Zian

Stacked ensemble formulates an ensemble using a meta-learner to combine (stack) the predictions of multiple base classifiers. It suffers from the problem of suboptimal performance in imbalanced classification. Several underlying difficulty factors are reported to be responsible for performance de...

Saved in:

書目詳細資料
主要作者:	Seng , Zian
格式:	Thesis
出版:	2021
主題:	QA75 Electronic computers. Computer science T Technology (General)
在線閱讀:	http://studentsrepo.um.edu.my/14776/1/Seng_Zian.pdf http://studentsrepo.um.edu.my/14776/2/Seng_Zian.pdf http://studentsrepo.um.edu.my/14776/
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!

相似書籍

A neighborhood undersampling stacked ensemble (NUS-SE) in imbalanced classification
由: Seng, Zian, et al.
出版: (2021)

An empirical evaluation of stacked ensembles with different meta-learners in imbalanced classification
由: Zian, Seng, et al.
出版: (2021)

Fuzzy distance-based undersampling technique for imbalanced flood data
由: Ku-Mahamud, Ku Ruhana, et al.
出版: (2016)

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

A conceptual model of enhanced undersampling technique
由: Zorkeflee, Maisarah, et al.
出版: (2014)

A direct ensemble classifier for imbalanced multiclass learning
由: Sainin, Mohd Shamrie, et al.
出版: (2012)

A direct ensemble classifier for learning imbalanced multiclass data
由: Samry @ Mohd Shamrie Sainin
出版: (2013)

FURIA stacking ensemble for ASD classification
由: Ainie Hayati, Noruzman, et al.
出版: (2022)

Development of bright and dark pulsed fiber laser based on nonlinear polarization rotation / Tiu Zian Cheak
由: Tiu, Zian Cheak
出版: (2015)

Sistem kerjaya / Tay Kim Seng
由: Tay, Kim Seng
出版: (2003)

New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*
由: Muslim, Much Aziz, et al.
出版: (2023)

New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning
由: Muslim, Much Aziz, et al.
出版: (2023)

New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning
由: Muslim, Much Aziz, et al.
出版: (2023)

New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning
由: Muslim, Much Aziz, et al.
出版: (2023)

New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*
由: Muslim, Much Aziz, et al.
出版: (2023)

New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning
由: Muslim, Much Aziz, et al.
出版: (2023)

New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*
由: Much Aziz Muslim, Much Aziz Muslim, et al.
出版: (2023)

New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*
由: Muslim, Much Aziz, et al.
出版: (2023)

Income Tax Preparation System / Ku Seng Lip
由: Ku, Seng Lip
出版: (2001)

Electronic Library System (ELS) / Loh Wei Seng
由: Loh , Wei Seng
出版: (2000)

Ensemble Meta Classifier with Sampling and Feature Selection for Data with Multiclass Imbalance Problem
由: Sainin, Mohd Shamrie, et al.
出版: (2021)

Learning styles useful in improving students' learning / Mak Kem Seng
由: Mak, Kem Seng
出版: (2002)

Enhanced Heterogeneous Stacked Ensemble Machine Learning Model For Detecting Nigerian Politically Motivated Cyberhate
由: Sallau, Mullah Nanlir
出版: (2023)

Software e-inventory management system / Chew Kok Seng
由: Chew , Kok Seng
出版: (2003)

Traffic Information System Kuala Lumpur / Tay Tick Seng
由: Tay , Tick Seng
出版: (2003)

Stacking gels: A method for maximising output for pulsed-field gel electrophoresis
由: Heng, S.K., et al.
出版: (2009)

Influence maximisation towards target users on social networks for information diffusion
由: Temitope, Olanrewaju Abdus-Samad, et al.
出版: (2018)

Sentiment classification with concept drift and imbalanced class distributions
由: Jalilvand, A., et al.
出版: (2016)

Fuzzy and smote resampling technique for imbalanced data sets
由: Zorkeflee, Maisarah, et al.
出版: (2015)

Evaluation of machine learning techniques for imbalanced data in IDS
由: Mokaramian, Shahram
出版: (2013)

Classification of Qur’anic topics based on imbalanced classification
由: Arkok, Bassam, et al.
出版: (2020)

Stacking Ensemble for Pill Image Classification
由: Ahammed F.A.A.B.S., et al.
出版: (2025)

Web services for e-Procurement system in the context of supply chain management / Yap Khay Seng
由: Yap, Khay Seng
出版: (2007)

Testing the minimal bounded space method on vision-based drone navigation / Yap Seng Kuang
由: Yap , Seng Kuang
出版: (2021)

Random Undersampling on Imbalance Time Series Data for Anomaly Detection
由: Saripuddin M., et al.
出版: (2023)

Evolutionary deep belief networks with bootstrap sampling for imbalanced class datasets
由: Amri, A’inur A’fifah, et al.
出版: (2019)

Diagnosis of COVID-19 on chest X-ray (CXR) images using CNN with transfer learning and integrated stacking ensemble learning
由: Low, Wai Sing, et al.
出版: (2024)

Learning with imbalanced datasets using fuzzy ARTMAP-based neural network models
由: Tan, S. C., et al.
出版: (2011)

Imbalanced Classification Methods for Student Grade Prediction : A Systematic Literature Review
由: Siti Dianah, Abdul Bujang, et al.
出版: (2023)

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