Active learning for class imbalance problem

Authors:
Seyda Ertekin;Jian Huang;C. Lee Giles
Affiliations:
The Pennsylvania State University, University Park, PA;The Pennsylvania State University, University Park, PA;The Pennsylvania State University, University Park, PA
Venue:
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Year:
2007

Citing 3
Cited 17

Support vector machine active learning with applications to text classification

The Journal of Machine Learning Research
Fast Kernel Classifiers with Online and Active Learning

The Journal of Machine Learning Research
SMOTE: synthetic minority over-sampling technique

Journal of Artificial Intelligence Research

Reducing False Alarm of Video-Based Smoke Detection by Support Vector Machine

PAISI, PACCF and SOCO '08 Proceedings of the IEEE ISI 2008 PAISI, PACCF, and SOCO international workshops on Intelligence and Security Informatics
Geometric Manifold Energy and Manifold Clustering

ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
Margin calibration in SVM class-imbalanced learning

Neurocomputing
Fast active tabu search and its application to image retrieval

IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
AdaOUBoost: adaptive over-sampling and under-sampling to boost the concept learning in large scale imbalanced data sets

Proceedings of the international conference on Multimedia information retrieval
RAMOBoost: ranked minority oversampling in boosting

IEEE Transactions on Neural Networks
Ensemble Learning with Active Example Selection for Imbalanced Biomedical Data Classification

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Incremental multiple classifier active learning for concept indexing in images and videos

MMM'11 Proceedings of the 17th international conference on Advances in multimedia modeling - Volume Part I
Differential optical flow applied to automatic facial expression recognition

Neurocomputing
Active learning for imbalanced sentiment classification

EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Simulation data mining for supporting bridge design

AusDM '11 Proceedings of the Ninth Australasian Data Mining Conference - Volume 121
Handling imbalanced data sets with synthetic boundary data generation using bootstrap re-sampling and AdaBoost techniques

Pattern Recognition Letters
Certainty-based active learning for sampling imbalanced datasets

Neurocomputing
Class imbalance and the curse of minority hubs

Knowledge-Based Systems
Boosted SVM for extracting rules from imbalanced data in application to prediction of the post-operative life expectancy in the lung cancer patients

Applied Soft Computing
Adjusted F-measure and kernel scaling for imbalanced data learning

Information Sciences: an International Journal
Imbalanced evolving self-organizing learning

Neurocomputing

Quantified Score

Hi-index	0.00

Visualization

Abstract

The class imbalance problem has been known to hinder the learning performance of classification algorithms. Various real-world classification tasks such as text categorization suffer from this phenomenon. We demonstrate that active learning is capable of solving the problem.