Multi-Imbalance: An open-source software for multi-class imbalance learning
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Hamido Fujita | Chongsheng Zhang | Enislay Ramentol | Baojun Qiao | Gaojuan Fan | Jingjun Bi | Shixin Xu | H. Fujita | Baojun Qiao | Enislay Ramentol | Chongsheng Zhang | Jingjun Bi | Gaojuan Fan | Shixin Xu
[1] Thomas G. Dietterich,et al. Error-Correcting Output Codes: A General Method for Improving Multiclass Inductive Learning Programs , 1991, AAAI.
[2] Luis Baumela,et al. Multi-class boosting with asymmetric binary weak-learners , 2014, Pattern Recognit..
[3] Xiangliang Zhang,et al. An up-to-date comparison of state-of-the-art classification algorithms , 2017, Expert Syst. Appl..
[4] Fan Yang,et al. CASQ: Adaptive and cloud-assisted query processing in vehicular sensor networks , 2019, Future Gener. Comput. Syst..
[5] Francisco Herrera,et al. IFROWANN: Imbalanced Fuzzy-Rough Ordered Weighted Average Nearest Neighbor Classification , 2015, IEEE Transactions on Fuzzy Systems.
[6] Tom Fawcett,et al. Adaptive Fraud Detection , 1997, Data Mining and Knowledge Discovery.
[7] Ming Li,et al. Constructing IGA-suitable planar parameterization from complex CAD boundary by domain partition and global/local optimization , 2017, ArXiv.
[8] Yoav Freund,et al. A decision-theoretic generalization of on-line learning and an application to boosting , 1997, EuroCOLT.
[9] Régis Duvigneau,et al. Analysis-suitable volume parameterization of multi-block computational domain in isogeometric applications , 2013, Comput. Aided Des..
[10] Robert Tibshirani,et al. Classification by Pairwise Coupling , 1997, NIPS.
[11] Huanhuan Chen,et al. Negative correlation learning for classification ensembles , 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).
[12] Yang Wang,et al. Boosting for Learning Multiple Classes with Imbalanced Class Distribution , 2006, Sixth International Conference on Data Mining (ICDM'06).
[13] You-Shyang Chen. An empirical study of a hybrid imbalanced-class DT-RST classification procedure to elucidate therapeutic effects in uremia patients , 2016, Medical & Biological Engineering & Computing.
[14] Zhi-Hua Zhou,et al. Learning Imbalanced Multi-class Data with Optimal Dichotomy Weights , 2013, 2013 IEEE 13th International Conference on Data Mining.
[15] Nitesh V. Chawla,et al. SMOTE: Synthetic Minority Over-sampling Technique , 2002, J. Artif. Intell. Res..
[16] Chongsheng Zhang,et al. An empirical comparison on state-of-the-art multi-class imbalance learning algorithms and a new diversified ensemble learning scheme , 2018, Knowl. Based Syst..
[17] Svetha Venkatesh,et al. Multi-class Pattern Classification in Imbalanced Data , 2010, 2010 20th International Conference on Pattern Recognition.
[18] Q. Henry Wu,et al. Association Rule Mining-Based Dissolved Gas Analysis for Fault Diagnosis of Power Transformers , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).
[19] Nicolás García-Pedrajas,et al. Improving multiclass pattern recognition by the combination of two strategies , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[20] Lawrence Mosley,et al. A balanced approach to the multi-class imbalance problem , 2013 .
[21] Xiangliang Zhang,et al. Abstracting massive data for lightweight intrusion detection in computer networks , 2016, Inf. Sci..
[22] Gustavo E. A. P. A. Batista,et al. A study of the behavior of several methods for balancing machine learning training data , 2004, SKDD.
[23] Yi Lu Murphey,et al. OAHO: an Effective Algorithm for Multi-Class Learning from Imbalanced Data , 2007, 2007 International Joint Conference on Neural Networks.
[24] Fernando Nogueira,et al. Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced Datasets in Machine Learning , 2016, J. Mach. Learn. Res..
[25] Sattar Hashemi,et al. To Combat Multi-Class Imbalanced Problems by Means of Over-Sampling Techniques , 2016, IEEE Transactions on Knowledge and Data Engineering.
[26] Ryan M. Rifkin,et al. In Defense of One-Vs-All Classification , 2004, J. Mach. Learn. Res..
[27] Kuan-Ching Li,et al. Urban Traffic Coulomb’s Law: A New Approach for Taxi Route Recommendation , 2019, IEEE Transactions on Intelligent Transportation Systems.
[28] María José del Jesús,et al. KEEL: a software tool to assess evolutionary algorithms for data mining problems , 2008, Soft Comput..
[29] Charlie C. L. Wang,et al. Isogeometric computation reuse method for complex objects with topology-consistent volumetric parameterization , 2016, Comput. Aided Des..
[30] Xiangliang Zhang,et al. Exploring Permission-Induced Risk in Android Applications for Malicious Application Detection , 2014, IEEE Transactions on Information Forensics and Security.
[31] Sungzoon Cho,et al. Constructing a multi-class classifier using one-against-one approach with different binary classifiers , 2015, Neurocomputing.
[32] Svetha Venkatesh,et al. Learning in imbalanced relational data , 2008, 2008 19th International Conference on Pattern Recognition.
[33] Yongdong Zhang,et al. Adaptive weighted imbalance learning with application to abnormal activity recognition , 2016, Neurocomputing.
[34] Lei Huang,et al. User Behavior Analysis and Video Popularity Prediction on a Large-Scale VoD System , 2018, ACM Trans. Multim. Comput. Commun. Appl..
[35] Trevor Hastie,et al. Multi-class AdaBoost ∗ , 2009 .
[36] Xiangliang Zhang,et al. Detecting Android malicious apps and categorizing benign apps with ensemble of classifiers , 2018, Future Gener. Comput. Syst..
[37] Liu Xiao,et al. Adapted ensemble classification algorithm based on multiple classifier system and feature selection for classifying multi-class imbalanced data , 2016 .