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[ Intro ] [ full-2 ] [ medium-1000 ]
[ medium-10000 ] [ medium-2000 ] [ medium-3000 ]
[ medium-4000 ] [ medium-5000 ] [ medium-6000 ]
[ medium-6000a-zero ] [ medium-6000a ] [ medium-6000b ]
[ medium-7000 ] [ medium-8000 ] [ medium-9000 ]
[ medium.2-1000 ] [ medium.2-10000 ] [ medium.2-2000 ]
[ medium.2-3000 ] [ medium.2-4000 ] [ medium.2-5000 ]
[ medium.2-6000 ] [ medium.2-7000 ] [ medium.2-8000 ]
[ medium.2-9000 ] [ optimal-1 ] [ optimal-1a ]
[ optimal-2 ] [ optimal-3 ] [ optimal-4 ]
[ optimal-5 ] [ optimal-5a ] [ optimal-6 ]
[ param-learn ] [ param-momentum ] [ parameter-matrix ]
[ paramselection-hidden ] [ short-1000 ] [ short-2000 ]
[ short-3000 ] [ short-4000 ] [ short-5000 ]
[ short-6000 ] [ short.2-1000 ] [ short.2-2000 ]
[ short.2-3000 ] [ short.2-4000 ] [ short.2-5000 ]
[ short.2-6000 ] [ simple-10000 ] [ simple-100000 ]
[ simple-2000 ] [ simple-5000 ]

[ Up: Report ] 

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7533291356645115	0.35421395076985074	age
Hidden Weights:
	0.022230836818651234	0.7390156300347646
	0.7053387476131181	-0.6615930936277854
		>50K		<=50K

Error sum for iteration 100 = 56.53903077212294

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7534190389057981	0.2575225599433837	age
Hidden Weights:
	-0.3985565572118925	1.2929288539669312
	0.2962230214597048	-0.1194084404399498
		>50K		<=50K

Error sum for iteration 200 = 60.95798426437753

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7535056857848805	0.048953666731644474	age
Hidden Weights:
	-0.496619941622068	1.429088741377744
	0.6725940425318022	-0.5420051252831414
		>50K		<=50K

Error sum for iteration 300 = 62.61371157690109

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7535925210434736	0.054720417369823984	age
Hidden Weights:
	-0.6266145995700053	1.581612169822905
	0.9641114222961011	-0.8965485721591911
		>50K		<=50K

Error sum for iteration 400 = 63.45167591033083

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.753669929057377	0.0719980232344843	age
Hidden Weights:
	-0.798073811890285	1.7625456213406083
	1.3542841369412832	-1.3117000442253661
		>50K		<=50K

Error sum for iteration 500 = 63.557041247887916

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537292175231811	0.10337876323632655	age
Hidden Weights:
	-0.9353556369449375	1.9060934530801588
	1.6666530038425944	-1.6394886884011326
		>50K		<=50K

Error sum for iteration 600 = 63.204112865141816

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537698351681479	0.13600452354315717	age
Hidden Weights:
	-1.0400164030546994	2.014706679502338
	1.896127705704513	-1.8783977005359496
		>50K		<=50K

Error sum for iteration 700 = 62.75241597440773

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537962031368544	0.16143751797449113	age
Hidden Weights:
	-1.1165484685064917	2.0937204927837247
	2.059648195426434	-2.0476856794466016
		>50K		<=50K

Error sum for iteration 800 = 62.35513077654005

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7538128609371851	0.1806538768913603	age
Hidden Weights:
	-1.1710490016852213	2.149814321746707
	2.174321510141606	-2.1659842503982314
		>50K		<=50K

Error sum for iteration 900 = 62.04594361722027

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7538230533361986	0.1956004913654748	age
Hidden Weights:
	-1.2091008570045803	2.188924252391391
	2.253732817277411	-2.2477651710822424
		>50K		<=50K

Error sum for iteration 1000 = 61.80960834862369

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7538288860908889	0.20759184870832675	age
Hidden Weights:
	-1.2349275549343077	2.2154774911899824
	2.307437203288044	-2.30307768098238
		>50K		<=50K

Error sum for iteration 1100 = 61.624539176192506

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7538317121337477	0.2174662315983339	age
Hidden Weights:
	-1.2515457867473805	2.2326093056823955
	2.342018364802936	-2.33878567080124
		>50K		<=50K

Error sum for iteration 1200 = 61.47992790668731

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7538324178167676	0.2257750115428935	age
Hidden Weights:
	-1.261100614346627	2.242535938862261
	2.362066295510347	-2.3596439768641133
		>50K		<=50K

Error sum for iteration 1300 = 61.36159955622029

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7538316013817666	0.23289436435629293	age
Hidden Weights:
	-1.2651355529143904	2.2468451852593714
	2.370840649385934	-2.369013202324474
		>50K		<=50K

Error sum for iteration 1400 = 61.26218257706775

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7538296802480198	0.23908967702761158	age
Hidden Weights:
	-1.2647830389901837	2.2466980126506413
	2.370708433062693	-2.3693245952563613
		>50K		<=50K

Error sum for iteration 1500 = 61.175196880508175

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7538269556040128	0.24455393332525677	age
Hidden Weights:
	-1.260894261085795	2.2429646070234015
	2.363433292360967	-2.362384146458864
		>50K		<=50K

Error sum for iteration 1600 = 61.09737616356705

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7538236519461415	0.249431374680329	age
Hidden Weights:
	-1.254126722625608	2.2363155044434775
	2.3503671325401227	-2.3495725690402
		>50K		<=50K

Error sum for iteration 1700 = 61.02659393059857

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7538199418325724	0.2538325307514291	age
Hidden Weights:
	-1.2450033657060364	2.2272828307585453
	2.332577834009207	-2.331977901704399
		>50K		<=50K

Error sum for iteration 1800 = 60.962205511417906

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7538159617408302	0.25784403149847285	age
Hidden Weights:
	-1.2339527929180736	2.2163018172594344
	2.3109352459363715	-2.310484457237654
		>50K		<=50K

Error sum for iteration 1900 = 60.90200200282511

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7538118224301197	0.26153517095410217	age
Hidden Weights:
	-1.2213368666601199	2.20373921416923
	2.286169711350523	-2.285833189646402
		>50K		<=50K

Error sum for iteration 2000 = 60.84517089324903

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7538076158076493	0.26496239098906815	age
Hidden Weights:
	-1.2074697245433914	2.189912831862069
	2.2589121495528297	-2.258662956891336
		>50K		<=50K

Error sum for iteration 2100 = 60.7907882051913

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.753803419503265	0.26817239509735313	age
Hidden Weights:
	-1.192630786194047	2.175104895177781
	2.229721385020947	-2.229538624718454
		>50K		<=50K

Error sum for iteration 2200 = 60.73832614860447

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.753799299900727	0.2712043343730046	age
Hidden Weights:
	-1.1770734009297787	2.1595709255033144
	2.199102330867435	-2.1989697698666815
		>50K		<=50K

Error sum for iteration 2300 = 60.68747689715909

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537953141065331	0.27409134847535305	age
Hidden Weights:
	-1.1610302182012557	2.143545272242177
	2.1675173686544476	-2.167422415158094
		>50K		<=50K

Error sum for iteration 2400 = 60.63795707868188

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537915111833094	0.27686164850856637	age
Hidden Weights:
	-1.1447160329567299	2.1272440707294145
	2.1353925296654572	-2.1353254579490812
		>50K		<=50K

Error sum for iteration 2500 = 60.58956477941107

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537879328828837	0.2795392709777045	age
Hidden Weights:
	-1.1283286865639994	2.1108662232553095
	2.1031196924472706	-2.1030730427855184
		>50K		<=50K

Error sum for iteration 2600 = 60.54238959985477

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.753784614059852	0.2821445973748359	age
Hidden Weights:
	-1.1120485343184956	2.0945929248015047
	2.0710558426466807	-2.0710239479081296
		>50K		<=50K

Error sum for iteration 2700 = 60.496513635010544

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.75378158291164	0.28469471312705863	age
Hidden Weights:
	-1.0960369779565036	2.078586239013044
	2.039520398019784	-2.039499004284063
		>50K		<=50K

Error sum for iteration 2800 = 60.45153455397017

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537788611638837	0.28720366629335237	age
Hidden Weights:
	-1.0804345665791042	2.0629872326187946
	2.008791602386613	-2.0087775615992984
		>50K		<=50K

Error sum for iteration 2900 = 60.40739037934869

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537764642946871	0.28968267611226434	age
Hidden Weights:
	-1.0653591580036816	2.047914163532341
	1.9791029676814402	-1.9790939874995666
		>50K		<=50K

Error sum for iteration 3000 = 60.365635386690805

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537744018625757	0.2921403313785064	age
Hidden Weights:
	-1.0509045802591737	2.0334611644268876
	1.9506406423530176	-1.9506350829652308
		>50K		<=50K

Error sum for iteration 3100 = 60.32518192077082

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537726779720074	0.2945828072506052	age
Hidden Weights:
	-1.0371401298505354	2.019697759670156
	1.9235423851321523	-1.9235390956704972
		>50K		<=50K

Error sum for iteration 3200 = 60.28584019764647

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537712918801204	0.2970141164927591	age
Hidden Weights:
	-1.0241110971580298	2.0066694066831214
	1.897898538083525	-1.8978967268329237
		>50K		<=50K

Error sum for iteration 3300 = 60.24853695804398

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537702387201399	0.2994363985005641	age
Hidden Weights:
	-1.011840342810747	1.9943990859105423
	1.8737550651712256	-1.8737541985855501
		>50K		<=50K

Error sum for iteration 3400 = 60.21271170351512

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537695102980808	0.3018502384772717	age
Hidden Weights:
	-1.0003307927829415	1.9828898073253196
	1.8511184121490365	-1.851118138078078
		>50K		<=50K

Error sum for iteration 3500 = 60.17809028468649

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537690959098047	0.30425500139322326	age
Hidden Weights:
	-0.9895686026748977	1.9721277840521778
	1.829961707018531	-1.8299617978148974
		>50K		<=50K

Error sum for iteration 3600 = 60.1444084306225

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537689831256685	0.3066491617475767	age
Hidden Weights:
	-0.9795266805285892	1.9620859626109612
	1.8102316933441231	-1.81023200482384
		>50K		<=50K

Error sum for iteration 3700 = 60.11157740940308

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537691584989504	0.30903061058460957	age
Hidden Weights:
	-0.9701682550238958	1.9527275968276934
	1.7918557778547441	-1.7918562204960171
		>50K		<=50K

Error sum for iteration 3800 = 60.08030022130786

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537696081677947	0.3113969248028297	age
Hidden Weights:
	-0.9614502211351171	1.9440095977420193
	1.7747486587666998	-1.7747491780419486
		>50K		<=50K

Error sum for iteration 3900 = 60.05026016366303

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.753770318335523	0.3137455891812663	age
Hidden Weights:
	-0.9533260696366369	1.935885466170454
	1.758818145781584	-1.7588187090801273
		>50K		<=50K

Error sum for iteration 4000 = 60.02118506456295

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537712756284001	0.3160741673464201	age
Hidden Weights:
	-0.9457482903016631	1.9283076980336047
	1.7439699472170884	-1.7439705353697932
		>50K		<=50K

Error sum for iteration 4100 = 59.993053427488334

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537724673395414	0.31838042302106584	age
Hidden Weights:
	-0.9386702151128793	1.9212296290039668
	1.7301113517890736	-1.7301119537086445
		>50K		<=50K

Error sum for iteration 4200 = 59.96550193637039

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537738815757797	0.3206623966863952	age
Hidden Weights:
	-0.9320473274313864	1.914606744616443
	1.7171538520155258	-1.7171544613840204
		>50K		<=50K

Error sum for iteration 4300 = 59.93852107186694

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537755073261145	0.3229184450505906	age
Hidden Weights:
	-0.9258381022576406	1.9083975211302386
	1.7050148353944412	-1.705015448659994
		>50K		<=50K

Error sum for iteration 4400 = 59.91218745460702

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537773344717505	0.32514725158076574	age
Hidden Weights:
	-0.9200044626330947	1.9025638823041788
	1.6936185103640626	-1.6936191255537454
		>50K		<=50K

Error sum for iteration 4500 = 59.88646322961347

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537793537552623	0.32734781614122416	age
Hidden Weights:
	-0.914511941775924	1.8970713617592918
	1.6828962441336428	-1.6828968601627432
		>50K		<=50K

Error sum for iteration 4600 = 59.86179292846114

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537815567236504	0.32951943086465035	age
Hidden Weights:
	-0.9093296345566136	1.8918890545895417
	1.67278647832023	-1.6727870945975365
		>50K		<=50K

Error sum for iteration 4700 = 59.83813978503576

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537839356579394	0.33166164810939225	age
Hidden Weights:
	-0.9044300099421752	1.8869894298844982
	1.6632343649863846	-1.6632349811920055
		>50K		<=50K

Error sum for iteration 4800 = 59.81562412337946

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537864834968434	0.3337742449913389	age
Hidden Weights:
	-0.8997886416720561	1.8823480614501642
	1.6541912373612142	-1.6541918533230415
		>50K		<=50K

Error sum for iteration 4900 = 59.79396307543564

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537891937613598	0.3358571877011206	age
Hidden Weights:
	-0.8953839001618124	1.8779433197381488
	1.6456140012514129	-1.645614616877725
		>50K		<=50K


Options: -I 5000 

Back Propagation Neural Network:
Numer Input Nodes: 1
Number Hidden Nodes: 2
Number Output Nodes: 2
	-I	5000
	-E	0.01
	-S	1623718248
	-H	2
	-M	0.01
Input Weights:
	0.7537920310605996	0.33789020909243733	age
Hidden Weights:
	-0.8912374894537933	1.8737969088124629
	1.6375439998195127	-1.6375446150661213
		>50K		<=50K



=== Error on training data ===

Correctly Classified Instances         387               77.4    %
Incorrectly Classified Instances       113               22.6    %
Mean absolute error                      0.3643
Root mean squared error                  0.4064
Relative absolute error                103.9638 %
Root relative squared error             97.173  %
Total Number of Instances              500     


=== Confusion Matrix ===

   a   b   <-- classified as
   0 113 |   a = >50K
   0 387 |   b = <=50K


=== Error on test data ===

Correctly Classified Instances         385               76.8463 %
Incorrectly Classified Instances       116               23.1537 %
Mean absolute error                      0.3606
Root mean squared error                  0.4066
Relative absolute error                102.0278 %
Root relative squared error             96.3881 %
Total Number of Instances              501     


=== Confusion Matrix ===

   a   b   <-- classified as
   0 116 |   a = >50K
   0 385 |   b = <=50K

by: Keith A. Pray
Last Modified: July 4, 2004 9:05 AM
© 2004 - 1975 Keith A. Pray.
All rights reserved.

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