Table 3.

Comparative analysis of prediction accuracies of different GS models for four yield related traits across chickpea population.

		ICRISAT-IR-13		ICRISAT-RF-13		IARI-IR-13		IARI-IR-12		ICRISAT-IR-12
	Methods	Correlations	SE	Correlations	SE	Correlations	SE	Correlations	SE	Correlations	SE
Days to flowering (DF)	Ridge Regression	0.665	0.005	0.556	0.006	0.674	0.005	0.663	0.006	0.823	0.003
	Kinship Gauss	0.707	0.005	0.635	0.005	0.673	0.005	0.701	0.006	0.847	0.003
	Bayes Cπ	0.663	0.005	0.564	0.006	0.675	0.005	0.663	0.006	0.824	0.003
	Bayes B	0.647	0.005	0.560	0.006	0.673	0.005	0.664	0.006	0.825	0.003
	Bayes LASSO	0.666	0.005	0.562	0.006	0.673	0.005	0.664	0.006	0.827	0.003
	Random Forest	0.693	0.005	0.626	0.006	0.683	0.004	0.695	0.006	0.851	0.003
Days to maturity (DM)	Ridge Regression	0.794	0.004	0.478	0.006	0.301	0.008	0.325	0.009	0.374	0.007
	Kinship Gauss	0.808	0.004	0.539	0.006	0.304	0.008	0.320	0.008	0.394	0.007
	Bayes Cπ	0.799	0.004	0.495	0.006	0.304	0.009	0.324	0.009	0.379	0.007
	Bayes B	0.798	0.004	0.510	0.006	0.289	0.009	0.331	0.009	0.395	0.007
	Bayes LASSO	0.797	0.004	0.476	0.006	0.301	0.008	0.329	0.009	0.376	0.007
	Random Forest	0.815	0.004	0.531	0.007	0.254	0.009	0.300	0.009	0.407	0.007
100 seed weight (SDW)	Ridge Regression	0.893	0.002	0.797	0.004	0.816	0.004	0.898	0.002	0.909	0.002
	Kinship Gauss	0.893	0.002	0.798	0.003	0.817	0.004	0.909	0.002	0.912	0.002
	Bayes Cπ	0.892	0.002	0.797	0.003	0.817	0.004	0.901	0.002	0.909	0.002
	Bayes B	0.887	0.002	0.792	0.004	0.816	0.004	0.903	0.002	0.908	0.002
	Bayes LASSO	0.892	0.002	0.799	0.004	0.817	0.004	0.900	0.002	0.909	0.002
	Random Forest	0.897	0.002	0.801	0.004	0.815	0.004	0.909	0.001	0.912	0.002
Seed yield (SY)	Ridge Regression	0.523	0.006	0.172	0.008	0.166	0.008	0.604	0.005	0.222	0.008
	Kinship Gauss	0.522	0.006	0.148	0.008	0.138	0.008	0.602	0.005	0.218	0.008
	Bayes Cπ	0.520	0.007	0.175	0.008	0.163	0.008	0.602	0.005	0.216	0.008
	Bayes B	0.517	0.006	0.171	0.008	0.168	0.008	0.597	0.005	0.209	0.009
	Bayes LASSO	0.524	0.006	0.182	0.008	0.163	0.007	0.598	0.006	0.216	0.008
	Random Forest	0.493	0.006	0.186	0.008	0.165	0.009	0.606	0.005	0.205	0.009

SE, Standard Error.