Table A3.

Comparison of selected mathematical models describing the shape of learning curves.

		${\mathit{MSE}}^{\left(\mathit{i}\right)}$			${\overline{\mathit{R}}}^2{}^{\left(\mathit{i}\right)}$			$\mathit{MSE}{}_{\mathit{predict}}^{\left(\mathit{i}\right)}$			${\overline{\mathit{R}}}^2{}_{\mathit{predict}}^{\left(\mathit{i}\right)}$
Algorithm	Quartile	Exp	Log	Pow	Exp	Log	Pow	Exp	Log	Pow	Exp	Log	Pow
Dataset: ada_prior
A	1	0.0056	0.0053	0.0053	0.0685	0.0165	0.0346	0.4736	0.5155	0.5065	−0.241	0.7041	0.3738
A	2	0.0078	0.0088		0.0682	0.0133		0.7629	0.7342		−0.235	0.7605
A	3	0.0094	0.0099		0.0110	0.0129		0.8045	0.7952		0.8005	0.7680
A	4	0.0102	0.0117	0.0116	0.0102	0.0117	0.0116	0.8159	0.7889	0.7894	0.8159	0.7889	0.7894
D	1	0.0012	0.0014	0.0008	0.0065	0.0766	0.0073	0.9085	0.9005	0.9432	0.7412	−2.025	0.7103
D	2	0.0019	0.0033	0.0012	0.0029	0.0241	0.0048	0.9102	0.8461	0.9425	0.8830	0.0473	0.8092
D	3	0.0024	0.0070	0.0022	0.0030	0.0094	0.0026	0.8957	0.6977	0.9024	0.8813	0.6272	0.8954
D	4	0.0029	0.0084	0.0026	0.0029	0.0084	0.0026	0.8837	0.6665	0.8957	0.8837	0.6665	0.8957
Dataset: analcatdata_halloffame
A	1		0.0007			0.0051			−0.098			−0.310
A	2		0.0015			0.0029			0.2211			0.2578
A	3	0.0020	0.0020	0.0020	0.0029	0.0029	0.0029	0.2693	0.2977	0.2718	0.2345	0.2592	0.2407
A	4	0.0029	0.0029	0.0029	0.0029	0.0029	0.0029	0.2414	0.2686	0.2497	0.2414	0.2686	0.2497
Dataset: car
B	1	0.0020	0.0028	0.0028	0.0183	0.1117	0.1047	0.9333	0.9180	0.9099	0.8465	0.0806	0.1209
B	2	0.0028	0.0070	0.0047	0.0209	0.0185	0.0061	0.9556	0.8948	0.9268	0.8249	0.8474	0.9491
B	3	0.0055	0.0087	0.0055	0.0085	0.0124	0.0058	0.9417	0.9112	0.9426	0.9283	0.8980	0.9515
B	4	0.0072	0.0108	0.0058	0.0072	0.0108	0.0058	0.9398	0.9114	0.9516	0.9398	0.9114	0.9516
D	1	0.0005	0.0022	0.0007	0.0191	0.1913	0.0158	0.9734	0.8998	0.9663	0.6635	−2.304	0.7225
D	2	0.0017	0.0111	0.0026	0.0302	0.0141	0.0256	0.9361	0.5910	0.9004	0.4674	0.7559	0.5487
D	3	0.0090	0.0138	0.0081	0.0198	0.0142	0.0143	0.7796	0.6724	0.8013	0.6508	0.7551	0.7479
D	4	0.0163	0.0141	0.0111	0.0163	0.0141	0.0111	0.7121	0.7563	0.8038	0.7121	0.7563	0.8038
Dataset: csb_ch12
D	1	0.0007	0.0007	0.0006	0.0030	0.0209	0.0012	0.7996	0.8040	0.8158	0.6773	−1.162	0.8777
D	2	0.0009	0.0010	0.0007	0.0010	0.0071	0.0018	0.8693	0.8627	0.8945	0.8901	0.2601	0.8051
D	3	0.0010	0.0017	0.0009	0.0010	0.0031	0.0011	0.8877	0.8073	0.9002	0.8903	0.6770	0.8862
D	4	0.0010	0.0025	0.0010	0.0010	0.0025	0.0010	0.8903	0.7413	0.8936	0.8903	0.7413	0.8936
Dataset: eye_movements
C	1		0.0077			0.1000			0.7201			−0.532
C	2	0.0068	0.0099		0.0258	0.0599		0.8394	0.7677		0.6027	0.0818
C	3	0.0151	0.0201	0.0199	0.0287	0.0514	0.0486	0.7616	0.6847	0.6852	0.5589	0.2117	0.2535
C	4	0.0236	0.0378	0.0338	0.0236	0.0378	0.0338	0.6368	0.4212	0.4806	0.6368	0.4212	0.4806
D	1	0.0049	0.0051	0.0037	0.1766	0.0123	0.0695	0.8208	0.8187	0.8644	−0.364	0.9054	0.4635
D	2	0.0122	0.0080	0.0077	0.0455	0.0134	0.0180	0.7874	0.8608	0.8654	0.6490	0.8971	0.8612
D	3	0.0148	0.0104		0.0177	0.0134		0.8623	0.9038		0.8634	0.8969
D	4	0.0157	0.0122	0.0121	0.0157	0.0122	0.0121	0.8786	0.9058	0.9064	0.8786	0.9058	0.9064
Dataset: genresTrain
A	1	0.0200	0.0142	0.0135	0.7900	0.0568	0.0321	0.9144	0.9398	0.9421	0.1544	0.9393	0.9656
A	2	0.0371	0.0194	0.0193	0.0969	0.0639	0.0548	0.9302	0.9638	0.9637	0.8963	0.9318	0.9414
A	3	0.0429	0.0288	0.0254	0.0669	0.0366	0.0280	0.9415	0.9608	0.9654	0.9284	0.9609	0.9700
A	4	0.0549	0.0340	0.0277	0.0549	0.0340	0.0277	0.9412	0.9637	0.9704	0.9412	0.9637	0.9704
C	1	0.0057	0.0060	0.0033	0.0174	0.1846	0.0248	0.6927	0.6792	0.8226	0.1473	−7.504	−0.144
C	2	0.0060	0.0128	0.0048	0.0066	0.0381	0.0107	0.6507	0.3569	0.7556	0.5267	−0.754	0.5068
C	3	0.0060	0.0177	0.0071	0.0060	0.0212	0.0082	0.5954	0.1677	0.6656	0.5692	0.0220	0.6212
C	4	0.0057	0.0198	0.0080	0.0057	0.0198	0.0080	0.5747	0.0896	0.6324	0.5747	0.0896	0.6324
D	1	0.0064	0.0066	0.0017	0.1963	0.1446	0.0124	0.9349	0.9336	0.9828	0.2269	0.4320	0.9512
D	2	0.0141	0.0102	0.0030	0.0393	0.0542	0.0043	0.9178	0.9407	0.9827	0.8451	0.7870	0.9830
D	3	0.0173	0.0161	0.0032	0.0231	0.0263	0.0037	0.9205	0.9265	0.9852	0.9091	0.8967	0.9856
D	4	0.0207	0.0219	0.0036	0.0207	0.0219	0.0036	0.9187	0.9140	0.9859	0.9187	0.9140	0.9859
Dataset: gina_prior
C	1	0.0014	0.0015	0.0015	0.0096	0.0959	0.0879	0.8734	0.8708	0.8655	0.4589	−4.369	−3.971
C	2	0.0024	0.0042	0.0030	0.0036	0.0235	0.0085	0.8480	0.7384	0.8069	0.7954	−0.316	0.5199
C	3	0.0029	0.0071	0.0041	0.0034	0.0110	0.0051	0.8295	0.5947	0.7622	0.8101	0.3850	0.7092
C	4	0.0033	0.0092	0.0048	0.0033	0.0092	0.0048	0.8145	0.4838	0.7307	0.8145	0.4838	0.7307
Dataset: kr-vs-kp
A	1	0.0037	0.0135	0.0027	0.0261	0.1384	0.0435	0.9012	0.6553	0.9286	0.1075	−0.843	0.4148
A	2	0.0118	0.0165	0.0064	0.0204	0.0511	0.0079	0.8002	0.7261	0.8911	0.7115	0.3189	0.8936
A	3	0.0145	0.0201	0.0069	0.0157	0.0289	0.0072	0.7903	0.7126	0.8997	0.7881	0.6152	0.9034
A	4	0.0153	0.0250	0.0072	0.0153	0.0250	0.0072	0.7940	0.6672	0.9034	0.7940	0.6672	0.9034
B	1	0.0022	0.0031	0.0029	0.0050	0.4181	0.2507	0.9620	0.9502	0.9510	0.9533	−2.847	−1.331
B	2	0.0024	0.0119	0.0054	0.0029	0.1028	0.0232	0.9730	0.8712	0.9403	0.9731	0.0537	0.7841
B	3	0.0027	0.0239	0.0079	0.0028	0.0399	0.0098	0.9731	0.7678	0.9224	0.9742	0.6331	0.9091
B	4	0.0028	0.0324	0.0089	0.0028	0.0324	0.0089	0.9743	0.7020	0.9172	0.9743	0.7020	0.9172
C	1		0.0049			0.0168			0.7999			0.8384
C	2	0.0067	0.0083		0.0083	0.0211		0.8900	0.8672		0.9190	0.7966
C	3	0.0071	0.0096	0.0093	0.0081	0.0141	0.0120	0.9171	0.8890	0.8913	0.9208	0.8638	0.8833
C	4	0.0081	0.0122	0.0107	0.0081	0.0122	0.0107	0.9213	0.8823	0.8959	0.9213	0.8823	0.8959
D	1	0.0006	0.0054	0.0007	0.0131	0.1433	0.0020	0.9763	0.7898	0.9699	0.6952	−2.293	0.9543
D	2	0.0016	0.0088	0.0009	0.0042	0.0319	0.0011	0.9537	0.7520	0.9745	0.9019	0.2661	0.9756
D	3	0.0023	0.0117	0.0009	0.0029	0.0163	0.0010	0.9428	0.7124	0.9763	0.9323	0.6250	0.9762
D	4	0.0028	0.0142	0.0010	0.0028	0.0142	0.0010	0.9361	0.6747	0.9762	0.9361	0.6747	0.9762