Abstract
Rare category detecion (RCD) aims to discover rare categories in a massive unlabeled data set with the help of a labeling oracle. A challenging task in RCD is to discover rare categories which are concealed by numerous data examples from major categories. Only a few algorithms have been proposed for this issue, most of which are on quadratic or cubic time complexity. In this paper, we propose a novel tree-based algorithm known as RCD-Forest with \(O(\varphi n \log {(n/s)})\) time complexity and high query efficiency where n is the size of the unlabeled data set. Experimental results on both synthetic and real data sets verify the effectiveness and efficiency of our method.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
References
Asuncion, A., Newman, D.: UCI Machine Learning Repository (2007)
Hao, H., Kevin, C., Yunjun, G., Qinming, H., Qing, L.: Rare category exploration. Expert Syst. Appl. 41(9), 4197–4210 (2014)
He, J., Carbonell, J.G.: Nearest-neighbor-based active learning for rare category detection. In: NIPS 2007, pp. 633–640 (2007)
He, J., Liu, Y., Lawrence, R.: Graph-based rare category detection. In: ICDE 2008, pp. 833–838 (2008)
Huang, H., He, Q., Chiew, K., Qian, F., Ma, L.: CLOVER: a faster prior-free approach to rare-category detection. Knowl. Inf. Syst. 35(3), 713–736 (2013)
Huang, H., He, Q., He, J., Ma, L.: RADAR: rare category detection via computation of boundary degree. In: Huang, J.Z., Srivastava, J., Cao, L. (eds.) PAKDD 2011, Part II. LNCS, vol. 6635, pp. 258–269. Springer, Heidelberg (2011)
Liu, F.T., Ting, K.M., Zhou, Z.H.: Isolation forest. In: ICDM 2008, pp. 413–422 (2008)
Liu, Z., Huang, H., He, Q., Chiew, K., Gao, Y.: Rare category exploration on linear time complexity. In: Renz, M., Shahabi, C., Zhou, X., Chemma, M.A. (eds.) DASFAA 2015. LNCS, vol. 9050, pp. 37–54. Springer, Heidelberg (2015)
Liu, Z., Huang, H., He, Q., Chiew, K., Ma, L.: Rare category detection on O(dN) time complexity. In: Ho, T.B., Zhou, Z.-H., Chen, A.L.P., Kao, H.-Y., Tseng, V.S. (eds.) PAKDD 2014, Part II. LNCS, vol. 8444, pp. 498–509. Springer, Heidelberg (2014)
Ram, P., Gray, A.G.: Density estimation trees. In: KDD 2011, pp. 627–635 (2011)
Weng, H.: Zhejiang University (2015). https://github.com/HaiQW/MOOC
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Weng, H., Liu, Z., Chiew, K., He, Q. (2015). Rare Category Detection Forest. In: Zhang, S., Wirsing, M., Zhang, Z. (eds) Knowledge Science, Engineering and Management. KSEM 2015. Lecture Notes in Computer Science(), vol 9403. Springer, Cham. https://doi.org/10.1007/978-3-319-25159-2_55
Download citation
DOI: https://doi.org/10.1007/978-3-319-25159-2_55
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-25158-5
Online ISBN: 978-3-319-25159-2
eBook Packages: Computer ScienceComputer Science (R0)