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Volumn 96, Issue 1, 2013, Pages 614-624

The gradient boosting algorithm and random boosting for genome-assisted evaluation in large data sets

Author keywords

Boosting; Genomic evaluation; Machine learning; Predictive ability

Indexed keywords

ALGORITHM; ANIMAL; ARTICLE; ARTIFICIAL INTELLIGENCE; BIOLOGICAL MODEL; CATTLE; GENETIC DATABASE; GENETICS; GENOME; GENOTYPE; MALE; PHENOTYPE; QUANTITATIVE TRAIT; SINGLE NUCLEOTIDE POLYMORPHISM;

EID: 84871610662     PISSN: 00220302     EISSN: 15253198     Source Type: Journal    
DOI: 10.3168/jds.2012-5630     Document Type: Article
Times cited : (42)

References (23)
  • 1
    • 77949293856 scopus 로고    scopus 로고
    • Hot topic: A unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score
    • Aguilar I., Misztal I., Johnson D.L., Legarra A., Tsuruta S., Lawlor T.J. Hot topic: A unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score. J. Dairy Sci. 2010, 93:743-752.
    • (2010) J. Dairy Sci. , vol.93 , pp. 743-752
    • Aguilar, I.1    Misztal, I.2    Johnson, D.L.3    Legarra, A.4    Tsuruta, S.5    Lawlor, T.J.6
  • 2
    • 33745157294 scopus 로고    scopus 로고
    • Boosting for high-dimensional linear models
    • Bühlmann P. Boosting for high-dimensional linear models. Ann. Stat. 2006, 34:559-583.
    • (2006) Ann. Stat. , vol.34 , pp. 559-583
    • Bühlmann, P.1
  • 4
    • 0002978642 scopus 로고    scopus 로고
    • Experiments with a new boosting algorithm
    • L. Saitta, ed. Morgan Kaufmann Publishers, Burlington, MA
    • Freund, Y., and R. E. Schapire. 1996. Experiments with a new boosting algorithm. Pages 158-156 in Thirteenth Int. Conf. Machine Learning. L. Saitta, ed. Morgan Kaufmann Publishers, Burlington, MA.
    • (1996) Thirteenth Int. Conf. Machine Learning , pp. 158-156
    • Freund, Y.1    Schapire, R.E.2
  • 5
    • 0035470889 scopus 로고    scopus 로고
    • Greedy functions approximation: A gradient boosting machine
    • Friedman J.H. Greedy functions approximation: A gradient boosting machine. Ann. Stat. 2001, 29:1189-1232.
    • (2001) Ann. Stat. , vol.29 , pp. 1189-1232
    • Friedman, J.H.1
  • 7
    • 33746424900 scopus 로고    scopus 로고
    • Genomic-assisted prediction of genetic value with semiparametric procedures
    • Gianola D., Fernando R.L., Stella A. Genomic-assisted prediction of genetic value with semiparametric procedures. Genetics 2006, 173:1761-1776.
    • (2006) Genetics , vol.173 , pp. 1761-1776
    • Gianola, D.1    Fernando, R.L.2    Stella, A.3
  • 8
    • 80053594474 scopus 로고    scopus 로고
    • Predicting complex quantitative traits with Bayesian neural networks: A case study with Jersey cows and wheat
    • Gianola D., Okut H., Weigel K.A., Rosa G.J.M. Predicting complex quantitative traits with Bayesian neural networks: A case study with Jersey cows and wheat. BMC Genet. 2011, 12:87.
    • (2011) BMC Genet. , vol.12 , pp. 87
    • Gianola, D.1    Okut, H.2    Weigel, K.A.3    Rosa, G.J.M.4
  • 9
    • 77953351710 scopus 로고    scopus 로고
    • An application of randomforest to a genome-wide association data set: Methodological considerations and new findings
    • Goldstein B.A., Hubbard A.E., Cutler A., Barcellos L.F. An application of randomforest to a genome-wide association data set: Methodological considerations and new findings. BMC Genet. 2010, 11:49.
    • (2010) BMC Genet. , vol.11 , pp. 49
    • Goldstein, B.A.1    Hubbard, A.E.2    Cutler, A.3    Barcellos, L.F.4
  • 10
    • 84858051043 scopus 로고    scopus 로고
    • Genome-wide prediction of discrete traits using Bayesian regressions and machine learning
    • González-Recio O., Forni S. Genome-wide prediction of discrete traits using Bayesian regressions and machine learning. Genet. Sel. Evol. 2011, 43:7.
    • (2011) Genet. Sel. Evol. , vol.43 , pp. 7
    • González-Recio, O.1    Forni, S.2
  • 11
    • 45849103551 scopus 로고    scopus 로고
    • Nonparametric methods for incorporating genomic information into genetic evaluations: An application to mortality in broilers
    • González-Recio O., Gianola D., Long N., Weigel K.A., Rosa G.J.M., Avendaño S. Nonparametric methods for incorporating genomic information into genetic evaluations: An application to mortality in broilers. Genetics 2008, 178:2305-2313.
    • (2008) Genetics , vol.178 , pp. 2305-2313
    • González-Recio, O.1    Gianola, D.2    Long, N.3    Weigel, K.A.4    Rosa, G.J.M.5    Avendaño, S.6
  • 12
    • 66249089985 scopus 로고    scopus 로고
    • Genome-assisted prediction of a quantitative trait measured in parents and progeny: Application to food conversion rate in chickens
    • González-Recio O., Gianola D., Rosa G.J.M., Weigel K.A., Kranis A. Genome-assisted prediction of a quantitative trait measured in parents and progeny: Application to food conversion rate in chickens. Genet. Sel. Evol. 2009, 41:3.
    • (2009) Genet. Sel. Evol. , vol.41 , pp. 3
    • González-Recio, O.1    Gianola, D.2    Rosa, G.J.M.3    Weigel, K.A.4    Kranis, A.5
  • 16
    • 0015000439 scopus 로고
    • Some results on Tchebycheffian spline functions
    • Kimeldorf G., Wahba G. Some results on Tchebycheffian spline functions. J. Math. Anal. Appl. 1971, 33:82-95.
    • (1971) J. Math. Anal. Appl. , vol.33 , pp. 82-95
    • Kimeldorf, G.1    Wahba, G.2
  • 18
    • 0035045051 scopus 로고    scopus 로고
    • Prediction of total genetic value using genome-wide dense marker maps
    • Meuwissen T.H.E., Hayes B.J., Goddard M.E. Prediction of total genetic value using genome-wide dense marker maps. Genetics 2001, 157:1819-1829.
    • (2001) Genetics , vol.157 , pp. 1819-1829
    • Meuwissen, T.H.E.1    Hayes, B.J.2    Goddard, M.E.3
  • 19
    • 0000570382 scopus 로고
    • On estimating regression
    • Nadaraya E.A. On estimating regression. Theory Probab. Appl. 1964, 9:141-142.
    • (1964) Theory Probab. Appl. , vol.9 , pp. 141-142
    • Nadaraya, E.A.1
  • 20
    • 77954187925 scopus 로고    scopus 로고
    • Genomic similarity and kernel methods II: Methods for genomic information
    • Schaid D.J. Genomic similarity and kernel methods II: Methods for genomic information. Hum. Hered. 2010, 70:132-140.
    • (2010) Hum. Hered. , vol.70 , pp. 132-140
    • Schaid, D.J.1
  • 23
    • 0001762424 scopus 로고
    • Smooth regression analysis
    • Watson G.S. Smooth regression analysis. Sankhya A 1964, 26:359-372.
    • (1964) Sankhya A , vol.26 , pp. 359-372
    • Watson, G.S.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.