메뉴 건너뛰기




Volumn 2016-January, Issue , 2016, Pages 955-960

Differentially private random forest with high utility

Author keywords

Decision trees; Differential privacy; Privacy preserving data mining; Random forest

Indexed keywords

CLASSIFICATION (OF INFORMATION); DATA MINING; DECISION MAKING; DECISION TREES;

EID: 84963568051     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2015.76     Document Type: Conference Paper
Times cited : (62)

References (26)
  • 1
    • 0041783510 scopus 로고    scopus 로고
    • Privacy-preserving data mining
    • ACM
    • R Agrawal and R Srikant. Privacy-preserving data mining. In ACM Sigmod Record, volume 29, pages 439-450. ACM, 2000
    • (2000) ACM Sigmod Record , vol.29 , pp. 439-450
    • Agrawal, R.1    Srikant, R.2
  • 3
    • 0035478854 scopus 로고    scopus 로고
    • Random forests
    • L Breiman. Random forests. Machine learning, 45(1):5-32, 2001
    • (2001) Machine Learning , vol.45 , Issue.1 , pp. 5-32
    • Breiman, L.1
  • 10
    • 33745556605 scopus 로고    scopus 로고
    • Calibrating noise to sensitivity in private data analysis
    • Springer
    • C Dwork, F McSherry, K Nissim, and A Smith. Calibrating noise to sensitivity in private data analysis. In Theory of Cryptography, pages 265-284. Springer, 2006
    • (2006) Theory of Cryptography , pp. 265-284
    • Dwork, C.1    McSherry, F.2    Nissim, K.3    Smith, A.4
  • 14
    • 84897484693 scopus 로고    scopus 로고
    • Machine-learning prediction of cancer survival: A retrospective study using electronic administrative records and a cancer registry
    • S Gupta et al. Machine-learning prediction of cancer survival: a retrospective study using electronic administrative records and a cancer registry. BMJ open, 4(3), 2014
    • (2014) BMJ Open , vol.4 , Issue.3
    • Gupta, S.1
  • 20
    • 34249966833 scopus 로고
    • An empirical comparison of selection measures for decisiontree induction
    • J Mingers. An empirical comparison of selection measures for decisiontree induction. Machine learning, 3(4):319-342, 1989
    • (1989) Machine Learning , vol.3 , Issue.4 , pp. 319-342
    • Mingers, J.1
  • 22
    • 33744584654 scopus 로고
    • Induction of decision trees
    • J R Quinlan. Induction of decision trees. Machine learning, 1(1):81-106, 1986
    • (1986) Machine Learning , vol.1 , Issue.1 , pp. 81-106
    • Quinlan, J.R.1
  • 24
    • 84924049094 scopus 로고    scopus 로고
    • A framework for feature extraction from hospital medical data with applications in risk prediction
    • T Tran et al. A framework for feature extraction from hospital medical data with applications in risk prediction. BMC bioinformatics, 15(1):6596, 2014
    • (2014) BMC Bioinformatics , vol.15 , Issue.1 , pp. 6596
    • Tran, T.1
  • 26
    • 84900435600 scopus 로고    scopus 로고
    • Minimaxity, statistical thinking and differential privacy
    • L Wasserman. Minimaxity, statistical thinking and differential privacy. Journal of Privacy and Confidentiality, 4(1):3, 2012
    • (2012) Journal of Privacy and Confidentiality , vol.4 , Issue.1 , pp. 3
    • Wasserman, L.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.