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Volumn 107, Issue 31, 2010, Pages 13559-13560

Boosting predictions of treatment success

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; FERTILIZATION IN VITRO; GENETIC ASSOCIATION; HUMAN; LIVE BIRTH; MEDICAL DECISION MAKING; MEDICAL LITERATURE; NOTE; PATIENT SELECTION; PRIORITY JOURNAL; STATISTICAL MODEL; TREATMENT OUTCOME; BIOMETRY; FEMALE; PHENOTYPE; PREGNANCY; PREGNANCY OUTCOME; PROBABILITY; STATISTICS;

EID: 77956383473     PISSN: 00278424     EISSN: 10916490     Source Type: Journal    
DOI: 10.1073/pnas.1008052107     Document Type: Note
Times cited : (10)

References (14)
  • 1
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    • Deep phenotyping to predict live birth outcomes in in vitro fertilization
    • Banerjee P, et al. (2010) Deep phenotyping to predict live birth outcomes in in vitro fertilization. Proc Natl Acad Sci USA 107:13570-13575.
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    • Banerjee, P.1
  • 3
    • 0034164230 scopus 로고    scopus 로고
    • ADDITIVE LOGISTIC REGRESSION: A STATISTICAL VIEW of BOOSTING
    • Friedman J, Hastie T, Tibshirani R (2000) Additive logistic regression: A statistical view of boosting. Ann Stat 28:337-407. (Pubitemid 33227445)
    • (2000) Annals of Statistics , vol.28 , Issue.2 SPI , pp. 337-407
    • Friedman, J.1    Hastie, T.2    Tibshirani, R.3
  • 5
    • 41549141939 scopus 로고    scopus 로고
    • Boosting algorithms: Regularization, prediction and model fitting
    • Buhlmann P, Hothorn T (2007) Boosting algorithms: Regularization, prediction and model fitting. Stat Sci 98:477-515.
    • (2007) Stat Sci , vol.98 , pp. 477-515
    • Buhlmann, P.1    Hothorn, T.2
  • 6
    • 85194972808 scopus 로고    scopus 로고
    • Regression shrinkage and selection via the lasso
    • Tibshirani R (1996) Regression shrinkage and selection via the lasso. J R Stat Soc Series B 58:267-288.
    • (1996) J R Stat Soc Series B , vol.58 , pp. 267-288
    • Tibshirani, R.1
  • 8
    • 0035470889 scopus 로고    scopus 로고
    • Greed function approximation: A gradient boosting machine
    • Friedman JH (2001) Greed function approximation: A gradient boosting machine. Ann Stat 29:1189-1232.
    • (2001) Ann Stat , vol.29 , pp. 1189-1232
    • Friedman, J.H.1
  • 10
    • 0007425929 scopus 로고    scopus 로고
    • Bump hunting in high dimensional data
    • Friedman J, Fisher N (1999) Bump hunting in high dimensional data. Stat Comput 9:123-143.
    • (1999) Stat Comput , vol.9 , pp. 123-143
    • Friedman, J.1    Fisher, N.2
  • 12
    • 77956385510 scopus 로고    scopus 로고
    • Risk prediction models for genome-wide association studies
    • in press
    • Kooperberg C, LeBlanc M, Obenchain V (2010) Risk prediction models for genome-wide association studies. Genet Epidemiol, in press.
    • (2010) Genet Epidemiol
    • Kooperberg, C.1    LeBlanc, M.2    Obenchain, V.3
  • 13
    • 77956367424 scopus 로고    scopus 로고
    • Variable selection for qualitative interactions
    • in press
    • Gunter L, Zhua J, Murphy SA (2010) Variable selection for qualitative interactions. Stat Methodol, in press.
    • (2010) Stat Methodol
    • Gunter, L.1    Zhua, J.2    Murphy, S.A.3
  • 14
    • 77955137081 scopus 로고    scopus 로고
    • Structures and Assumptions: Strategies to Harness Gene x Gene and Gene x Environment Interactions in GWAS
    • Kooperberg C et al. (2009) Structures and Assumptions: Strategies to Harness Gene x Gene and Gene x Environment Interactions in GWAS. Stat Sci 24:472-488.
    • (2009) Stat Sci , vol.24 , pp. 472-488
    • Kooperberg, C.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.