Reality of Time Series Learning Data Collection

Author:

Ninagawa Chuzo

Publisher

Springer Nature Singapore

Reference15 articles.

1. M. Priyadarshana, G. Sofronov, Multiple break-points detection in array CGH data via cross-entropy method. IEEE/ACM Trans. Comput. Biol. Bioinform. 12(2), 487–498 (2015)

2. N. Zhang, G. David, O. Siegmund, A modified Bayes information criterion with applications to the analysis of comparative genomic hybridization data. Biometrics 63, 22–32 (2007)

3. M. Priyadarshana, G. Sofronov, Multiple Break-Point Detection via the Cross-Entropy Method. R Package “breakpoint” (2014). https://github.com/madawaweer

4. S.J. Yen, Y.S. Lee, Cluster-based under-sampling approaches for imbalanced data distributions. Expert Syst. Appl. 36(3), 5718–5727 (2009)

5. M. Kubat, S. Matwin, Addressing the curse of imbalanced training sets: one-sided selection, in ICML, ed. D.H. Fisher (Morgan Kaufmann, 1997), pp. 179–186

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