notesum.ai

Published at November 25

Effective Non-Random Extreme Learning Machine

stat.ML

Released Date: November 25, 2024

Authors: Daniela De Canditiis¹, Fabiano Veglianti²

Aff.: ¹Istituto per le Applicazioni del Calcolo, CNR, via dei Taurini 19, Rome, 00185, Italy; ²Department of Computer, Control, and Management Engineering Antonio Ruberti, Sapienza University of Rome, Italy

Arxiv: http://arxiv.org/abs/2411.16229v1

Dataset	A-ENR-ELM	I-ENR-ELM	ELM (20 iterations)	ELM (1 iteration)
Dataset 1	16.32146	124.96869	5307.37014	265.36851
Dataset 2	14.18106	140.60400	3787.67999	189.38400
Dataset 3	14.54270	117.02895	3738.63963	186.93198
Dataset 4	14.25233	121.38743	4370.76972	218.53849
Dataset 5	14.08346	105.09719	3819.09180	190.95459
Dataset 6	14.75797	107.49984	3645.48390	182.27419
Dataset 7	15.93076	115.34181	3760.09064	188.00453
Dataset 8	13.86249	114.22304	3777.84259	188.89213
Dataset 9	14.53062	94.65098	3748.16894	187.40845
Dataset 10	13.96850	143.14260	3757.50901	187.87545
Dataset 11	14.24737	106.52110	6491.89338	324.59467
Dataset 12	14.36173	136.39106	5169.10815	258.45541
Dataset 13	20.54475	333.03524	6069.08772	303.45439
Dataset 14	24.03600	435.90489	5367.00658	268.35033
Dataset 15	16.05688	335.69949	4970.70184	248.53509
Dataset 16	16.03769	408.20349	4678.19782	233.90989
Dataset 17	15.10580	278.86309	4474.52763	223.72638
Dataset 18	18.08123	403.01774	4430.76436	221.53822
Dataset 19	15.46903	312.33403	4566.51599	228.32580
Dataset 20	15.08143	369.08719	4375.69521	218.78476
Dataset 21	17.08805	329.02546	4371.82896	218.59145
Dataset 22	16.03508	370.74961	4475.03478	223.75174
Dataset 23	15.17585	262.05518	4395.86727	219.79336
Dataset 24	15.59896	300.90870	4304.27108	215.21355
Dataset 25	338.16093	687.32146	135352.25036	6767.61252
Dataset 26	325.93514	748.87876	130395.48539	6519.77427
Dataset 27	335.48370	764.41084	130706.77772	6535.33889
Dataset 28	329.64922	715.07219	131380.34171	6569.01709
Dataset 29	321.74117	595.92242	132626.76983	6631.33849
Dataset 30	326.42065	730.79328	128876.64502	6443.83225
Dataset 31	331.72239	666.00263	129583.91208	6479.19560
Dataset 32	321.78727	692.16751	130419.67952	6520.98398
Dataset 33	329.06390	717.21019	130369.22295	6518.46115
Dataset 34	328.76441	697.19879	131257.85343	6562.89267
Dataset 35	330.05414	579.63691	132284.08713	6614.20436
Dataset 36	325.93300	694.37587	150845.70616	7542.28531
Dataset 37	357.21692	1448.53690	140409.61809	7020.48090
Dataset 38	345.47655	1598.43018	138844.50821	6942.22541
Dataset 39	344.23160	1365.46915	140113.51526	7005.67576
Dataset 40	349.53607	1652.66787	142978.33630	7148.91681
Dataset 41	342.46273	1050.00356	138376.15035	6918.80752
Dataset 42	344.69478	1194.74726	139728.52306	6986.42615
Dataset 43	347.03367	1358.38221	137371.92784	6868.59639
Dataset 44	350.87913	1350.14249	141273.82691	7063.69135
Dataset 45	346.11636	1254.28499	141724.36133	7086.21807
Dataset 46	358.33137	1608.32152	138566.31555	6928.31578
Dataset 47	342.84621	1152.46139	140474.07547	7023.70377
Dataset 48	353.20407	1135.06300	139754.34675	6987.71734
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