Combining Sampling and Ensemble Classifier for Multiclass Imbalance Data Learning

Mohd Shamrie Sainin; Rayner Alfred; Fairuz Adnan; Faudziah Ahmad

doi:10.1007/978-981-10-8276-4_25

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Combining Sampling and Ensemble Classifier for Multiclass Imbalance Data Learning

Mohd Shamrie Sainin Rayner Alfred Fairuz Adnan Faudziah Ahmad

Year: 2018 Lecture notes in electrical engineering Pages: 262-272 Publisher: Springer Science+Business Media

DOI: 10.1007/978-981-10-8276-4_25

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Keywords:

Ensemble learning Random forest Naive Bayes classifier Computer science Artificial intelligence Machine learning C4.5 algorithm Classifier (UML) Cascading classifiers Random subspace method Pattern recognition (psychology) Probabilistic classification Multiclass classification Oversampling Statistical classification Support vector machine

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Imbalanced Data Classification Techniques

Physical Sciences → Computer Science → Artificial Intelligence

Data Mining Algorithms and Applications

Physical Sciences → Computer Science → Information Systems

Financial Distress and Bankruptcy Prediction

Social Sciences → Business, Management and Accounting → Accounting

Combining Sampling and Ensemble Classifier for Multiclass Imbalance Data Learning

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