Table 3 Results of a performance evaluation using the developed ML techniques during testing phase.

From: Developing machine learning algorithms for meteorological temperature and humidity forecasting at Terengganu state in Malaysia

	MLP			RBF			GBT			RF			LR
	R	MAE	RMSE	R	MAE	RMSE	R	MAE	RMSE	R	MAE	RMSE	R	MAE	RMSE
M1	0.695	0.019	0.027	0.691	0.019	0.027	0.692	0.019	0.027	0.694	0.019	0.027	0.656	0.019	0.027
M2	0.702	0.018	0.027	0.677	0.019	0.028	0.699	0.019	0.027	0.701	0.019	0.027	0.671	0.019	0.023
M3	0.707	0.018	0.026	0.435	0.032	0.036	0.704	0.018	0.027	0.703	0.019	0.027	0.678	0.019	0.026
M4	0.709	0.018	0.026	0.444	0.031	0.034	0.706	0.018	0.026	0.704	0.019	0.027	0.686	0.018	0.026
M5	0.710	0.018	0.026	0.488	0.024	0.033	0.709	0.018	0.026	0.697	0.019	0.027	0.686	0.018	0.026
M6	0.713	0.018	0.026	0.433	0.037	0.032	0.711	0.018	0.026	0.697	0.019	0.027	0.686	0.018	0.026
M7	0.609	0.027	0.040	0.591	0.027	0.041	0.597	0.028	0.041	0.611	0.027	0.040	0.575	0.027	0.040
M8	0.618	0.027	0.040	0.544	0.029	0.043	0.607	0.027	0.041	0.623	0.027	0.040	0.583	0.027	0.040
M9	0.624	0.027	0.040	0.458	0.029	0.029	0.610	0.027	0.040	0.627	0.027	0.040	0.592	0.027	0.040
M10	0.624	0.027	0.040	0.408	0.042	0.037	0.612	0.027	0.040	0.629	0.026	0.040	0.613	0.027	0.040
M11	0.625	0.026	0.040	0.434	0.039	0.035	0.613	0.027	0.040	0.631	0.026	0.040	0.614	0.027	0.040
M12	0.634	0.026	0.039	0.472	0.023	0.029	0.615	0.027	0.040	0.631	0.026	0.040	0.616	0.026	0.040
M13	0.767	0.013	0.016	0.784	0.013	0.016	0.782	0.013	0.016	0.776	0.013	0.016	0.735	0.013	0.016
M14	0.786	0.012	0.016	0.801	0.012	0.015	0.801	0.012	0.015	0.807	0.012	0.015	0.748	0.012	0.016
M15	0.828	0.011	0.014	0.830	0.011	0.014	0.818	0.011	0.015	0.840	0.011	0.014	0.768	0.012	0.015
M16	0.846	0.011	0.014	0.832	0.011	0.014	0.830	0.011	0.014	0.840	0.011	0.014	0.775	0.012	0.015
M17	0.582	0.018	0.023	0.614	0.017	0.023	0.639	0.017	0.022	0.618	0.017	0.023	0.528	0.018	0.023
M18	0.655	0.017	0.022	0.666	0.016	0.021	0.632	0.017	0.022	0.662	0.017	0.021	0.529	0.018	0.023
M19	0.670	0.016	0.021	0.703	0.016	0.020	0.646	0.017	0.022	0.702	0.016	0.021	0.536	0.018	0.023
M20	0.651	0.017	0.022	0.713	0.015	0.020	0.653	0.017	0.022	0.684	0.016	0.021	0.539	0.018	0.023

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Table 3 Results of a performance evaluation using the developed ML techniques during testing phase.

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