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Volumn , Issue , 2011, Pages 1215-1218

Nearest neighbor voting in high-dimensional data: Learning from past occurrences

Author keywords

[No Author keywords available]

Indexed keywords

CURSE OF DIMENSIONALITY; HIGH DIMENSIONAL DATA; HIGH-DIMENSIONAL; INFORMATIVENESS; NEAREST NEIGHBOR CLASSIFICATION; NEAREST NEIGHBOR METHOD; NEAREST NEIGHBORS; NEAREST-NEIGHBOR APPROACHES;

EID: 84857152681     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDMW.2011.127     Document Type: Conference Paper
Times cited : (9)

References (11)
  • 9
    • 83055186753 scopus 로고    scopus 로고
    • A probabilistic approach to nearest-neighbor classification: Naive hubness bayesian knn
    • N. Tomašev, M. Radovanović, D. Mladenić, and M. Ivanović, "A probabilistic approach to nearest-neighbor classification: Naive hubness bayesian knn," in CIKM conference, 2011.
    • (2011) CIKM Conference
    • Tomašev, N.1    Radovanović, M.2    Mladenić, D.3    Ivanović, M.4
  • 10
    • 70449440398 scopus 로고    scopus 로고
    • Fast approximate kNN graph construction for high dimensional data via recursive Lanczos bisection
    • J. Chen, H. ren Fang, and Y. Saad, "Fast approximate kNN graph construction for high dimensional data via recursive Lanczos bisection," Journal of Machine Learning Research, vol. 10, pp. 1989-2012, 2009.
    • (2009) Journal of Machine Learning Research , vol.10 , pp. 1989-2012
    • Chen, J.1    Ren Fang, H.2    Saad, Y.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.