Author:
Sinciya P. O.,Mary Amala Bai V.,Jeya A Celin J.
Reference13 articles.
1. Seiffert C, Khoshgoftaar TM, Van Hulse J (2007) An empirical study of the classification performance of learners on imbalanced and noisy software quality data. In: Procedings of IEEE international conference on information reuse and integration, pp 651–658
2. Napierala K, Stefanowski J, Wilk S (2010) Learning from imbalanced data in presence of noisy and borderline examples. In: Proceedings of 7th international conference on rough sets and current trends in computing (RSCTC2010), pp 158–167
3. Peng L, Zhang H, Yang B, Chen Y, Qassrawi Y, Lu G (2012) Traffic identification using flexible neural trees. In: Proceeding of the 18th international workshop of QoS (IWQoS 2012), pp 1–5
4. García V, Mollineda RA, Sánchez JS (2008) On the k-NN performance in a challenging scenario of imbalance and overlapping. Pattern Anal Appl 11:269–280
5. Cano A, Zafra A, Ventura S (2013) Weighted data gravitation classification for standard and imbalanced data. IEEE Trans Cybern 1–16