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Incremental learning from unbalanced data
2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541)
An ensemble based algorithm, LearnU.MT2, is introduced as an enhanced alternative to our previously reported incremental learning algorithm, Learn++. Both algorithms are capable of incrementally learning novel information from new datasets that consecutively become available, without requiring access to the previously seen data. In this contribution, we describe LearnH.MT2 which specifically targets incrementally learning from distinctly unbalanced data, where the amount of data that become
doi:10.1109/ijcnn.2004.1380080
fatcat:jnyz3t7pprb6fklwtptegcps3y