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Binary and multiclass imbalanced classification using multi-objective ant programming | IEEE Conference Publication | IEEE Xplore

Binary and multiclass imbalanced classification using multi-objective ant programming


Abstract:

Classification in imbalanced domains is a challenging task, since most of its real domain applications present skewed distributions of data. However, there are still some...Show More

Abstract:

Classification in imbalanced domains is a challenging task, since most of its real domain applications present skewed distributions of data. However, there are still some open issues in this kind of problem. This paper presents a multi-objective grammar-based ant programming algorithm for imbalanced classification, capable of addressing this task from both the binary and multiclass sides, unlike most of the solutions presented so far. We carry out two experimental studies comparing our algorithm against binary and multiclass solutions, demonstrating that it achieves an excellent performance for both binary and multiclass imbalanced data sets.
Date of Conference: 27-29 November 2012
Date Added to IEEE Xplore: 24 January 2013
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Conference Location: Kochi, India

References

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