A comparison of random forests, boosting and support vector machines for genomic selection

BMC Proceedings

Table 1

CV/TBV	Sample size		Random Forests		Boosting		Support Vector Machines		Ridge Regression BLUP
	Mean	Range	Mean	Range	Mean	Range	Mean	Range	Mean	Range
CV	439	416-514	0.466	0.392-0.534	0.503	0.431-0.567	0.503	0.432-0.567	0.530	0.451-0.620
TBV	900		0.483		0.547		0.497		0.607

Predictive accuracies of random forests, boosted regression trees, epsilon support vector machines and RR-BLUP, expressed as the Pearson correlation between GEBVs and observed values from the 5-fold cross-validation (CV) and between GEBVs and TBV for non-phenotyped individuals (TBV).

ISSN: 1753-6561