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Experiments
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.6826666355522275 -0.06981821235373165 age
0.42049110765850606 -0.4555620118007213 workclass=Private
-0.1506853402550452 0.9557247982659063 workclass=Self-emp-not-inc
0.5480060506666911 0.45295506240719785 workclass=Self-emp-inc
-0.4132263126624822 -0.12535182209567375 workclass=Federal-gov
0.9735455686949264 0.5168596666032232 workclass=Local-gov
0.28637389307025374 0.6076404802085325 workclass=State-gov
-0.18103021086285875 0.5927992043490469 workclass=Without-pay
0.9526107472575105 0.4694953163607096 workclass=Never-worked
0.5377166875735322 0.5342374298498833 fnlwgt
0.7919445086209878 0.12025428203320443 education=Bachelors
-0.7157235444125449 0.23445203161964412 education=Some-college
0.8686805170085108 0.7244094429294028 education=11th
-0.13017592686030333 0.7205046152833785 education=HS-grad
0.8926613332873206 0.8266018628385161 education=Prof-school
0.7756985789904645 -0.6563878125732463 education=Assoc-acdm
0.36333055734518727 -0.6056293607323935 education=Assoc-voc
-0.031758258782021764 0.5321623324194169 education=9th
-0.3424420844844913 0.423428644951896 education=7th-8th
-0.14068095501192923 0.7247779691118375 education=12th
0.4585915867636856 0.08343844088717933 education=Masters
-0.02235294181387104 -0.4610165953350156 education=1st-4th
-0.8564889015256045 -0.2941524548152903 education=10th
0.016613288155816308 0.2315519179542478 education=Doctorate
0.5582384838855585 0.052282124592665236 education=5th-6th
0.6331163202213776 -0.43634143162443473 education=Preschool
0.9129148182496716 0.7933077273133975 education-num
0.38633289440283813 0.5104175220395812 marital-status=Married-civ-spouse
0.4454034554922097 0.4828127653572949 marital-status=Divorced
0.6912598684411237 -0.7181142992587322 marital-status=Never-married
-0.13526650579944155 -0.48863403655016757 marital-status=Separated
0.7541398000390263 0.0015599254010263408 marital-status=Widowed
0.45608718315459673 -0.49008491018762435 marital-status=Married-spouse-absent
-0.24101975041037105 0.487920101439854 marital-status=Married-AF-spouse
-0.12015019869477972 0.8691396432786747 occupation=Tech-support
-0.34141652605560635 0.9925675190590553 occupation=Craft-repair
-0.8765717102002892 0.8244161969360466 occupation=Other-service
-0.16917251545893075 0.7716177043199333 occupation=Sales
-0.5211111811265918 -0.21478680074087086 occupation=Exec-managerial
-0.39884775367203984 0.030618308803817662 occupation=Prof-specialty
0.7536074814116316 0.08307133074887219 occupation=Handlers-cleaners
-0.3161834310584708 -0.6684797200936645 occupation=Machine-op-inspct
0.8254647249646943 -0.6348410390695995 occupation=Adm-clerical
-0.5952280390383271 0.9460186759703446 occupation=Farming-fishing
0.9977788474739098 0.7304850447525648 occupation=Transport-moving
-0.9460381843643757 -0.9354540810380978 occupation=Priv-house-serv
-0.019937433375414093 0.12172550071427746 occupation=Protective-serv
-0.2407354041314671 -0.8752702763934186 occupation=Armed-Forces
0.5254360632450226 0.14452835339022352 relationship=Wife
-0.7683249725342165 0.9263649049275988 relationship=Own-child
0.3195334706275028 -0.44586445418047305 relationship=Husband
-0.0760789604069021 -0.5102193808337288 relationship=Not-in-family
-0.6168637764338729 0.260952414462563 relationship=Other-relative
-0.6364369737310624 -0.1524440113547385 relationship=Unmarried
0.4844464909578581 0.4658270790553749 race=White
-0.5735175710778333 -0.0887656976300153 race=Asian-Pac-Islander
-0.46147886418390605 0.014540295867097486 race=Amer-Indian-Eskimo
-0.6639471939464849 -0.7808462752488416 race=Other
-0.8986937066621106 0.3003625043347049 race=Black
0.40446472016053026 0.4616374906798426 sex
0.46308974443480033 0.05327797664340106 capital-gain
0.6416615085944919 -0.8727861440907927 capital-loss
0.8489126364908737 0.6131194454151967 hours-per-week
-0.021097208896605935 -0.9313493125380119 native-country=United-States
0.3981928354683899 -0.7613316135442709 native-country=Cambodia
0.09161985612813295 0.11953817563042946 native-country=England
0.19790047534868238 -0.4282304154890004 native-country=Puerto-Rico
-0.26777016199060943 -0.3111784449141817 native-country=Canada
0.1772350646876235 -0.560549659872398 native-country=Germany
-0.3610514809805061 -0.6712828456655369 native-country=Outlying-US(Guam-USVI-etc)
0.3497683774442941 -0.9085591158183608 native-country=India
0.9811493134911382 0.13622919575678627 native-country=Japan
-0.856913776496508 0.057627360416214524 native-country=Greece
0.9139764905635788 -0.7458367428102657 native-country=South
-0.4635339318421252 -0.1391498721203721 native-country=China
0.09199674983932549 -0.8530071381887461 native-country=Cuba
-0.19678123541632075 0.5948498575183039 native-country=Iran
-0.650317328639719 -0.5781758393792351 native-country=Honduras
0.9138790784710924 0.1035830278071157 native-country=Philippines
-0.4197699985259471 0.14540466598276636 native-country=Italy
-0.5938957514619341 0.3738364414952742 native-country=Poland
-0.012869190072092529 -0.5062196056079331 native-country=Jamaica
-0.2076869258847749 -0.5559106842168475 native-country=Vietnam
0.16732633578785805 0.49971147413968997 native-country=Mexico
0.6009169482448065 -0.7263405110355692 native-country=Portugal
-0.7983399775173956 -0.8090523908297189 native-country=Ireland
0.8943469380203595 -0.2891477495876915 native-country=France
0.3375058473989312 -0.18466443666590915 native-country=Dominican-Republic
-0.24139134364616743 0.019361743036187207 native-country=Laos
-0.321616862492778 -0.37938078140746057 native-country=Ecuador
0.7151883930999234 -0.09041952244548268 native-country=Taiwan
-0.7566584147293793 -0.9894088917746124 native-country=Haiti
0.3859346352202955 -0.8144893873340981 native-country=Columbia
-0.009065012788254556 0.266601186175883 native-country=Hungary
-0.11706726586345328 0.9371631579474327 native-country=Guatemala
0.05345664140244111 -0.4452819606240157 native-country=Nicaragua
0.3550252262773288 0.6299377855542057 native-country=Scotland
-0.8996945811240489 0.0032055817622433924 native-country=Thailand
-0.32411062289516934 0.8825176957226781 native-country=Yugoslavia
0.017150085079070898 -0.6796797685337161 native-country=El-Salvador
-0.6003855260657207 -0.4319478318541059 native-country=Trinadad&Tobago
-0.009020196414839532 -0.9646139491733858 native-country=Peru
-0.448591727070744 -0.02664809284042935 native-country=Hong
0.6399327464428113 0.012061745375744115 native-country=Holand-Netherlands
Hidden Weights:
-0.500497225630351 -0.3541866361635895
0.6754020649086019 -0.621748300839374
>50K <=50K
Error sum for iteration 100 = 68.79754107722015
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.705682642454158 0.0465544371694322 age
0.7126059045852103 -0.9482022120749819 workclass=Private
-0.11690352109065041 0.8481883568634638 workclass=Self-emp-not-inc
0.5350103371481806 0.4971189768307462 workclass=Self-emp-inc
-0.39491760464791986 -0.04265754388870547 workclass=Federal-gov
1.0152702699977616 0.3538997639570409 workclass=Local-gov
0.31588868633365275 0.6016171752405983 workclass=State-gov
-0.1522838462090468 0.5469205145876066 workclass=Without-pay
0.9813571119113264 0.4236166265992579 workclass=Never-worked
0.5803415416163006 0.44618079499090857 fnlwgt
0.7847418245873965 0.351270374370545 education=Bachelors
-0.5982378883627726 -0.022193105924672926 education=Some-college
0.9209328086587062 0.4998260286002191 education=11th
0.043370291465639726 0.06753675432607455 education=HS-grad
0.9139225122502964 0.8893308123873871 education=Prof-school
0.8069476946705945 -0.6464717000900743 education=Assoc-acdm
0.3791350839306329 -0.549700841318367 education=Assoc-voc
0.022635079734048706 0.41402524920837624 education=9th
-0.3125345556743169 0.38294608533652436 education=7th-8th
-0.11299173426095711 0.7024620251625655 education=12th
0.46154023263390426 0.21054179950192664 education=Masters
0.013622625338743585 -0.5472711954204643 education=1st-4th
-0.8016276116657273 -0.4105703999426415 education=10th
0.025586147911772012 0.31607936976738193 education=Doctorate
0.599807449570221 -0.05467413602410444 education=5th-6th
0.6623153522915037 -0.48388966467443734 education=Preschool
1.0062901961023862 0.9627106638749084 education-num
0.2594750915450482 1.458901215573266 marital-status=Married-civ-spouse
0.5538565404464196 0.13726349731470222 marital-status=Divorced
0.9521565593626427 -1.5829181671480703 marital-status=Never-married
-0.07496197394342681 -0.621718247013802 marital-status=Separated
0.8049394380932657 -0.12235798303072057 marital-status=Widowed
0.5040826609951368 -0.605786622887382 marital-status=Married-spouse-absent
-0.21141590137188213 0.4343130290114619 marital-status=Married-AF-spouse
-0.08136978724876635 0.8381380241026403 occupation=Tech-support
-0.23184889335490994 0.6993910372923731 occupation=Craft-repair
-0.7149644217778706 0.45494296078230995 occupation=Other-service
-0.08913501931932598 0.5244375286818183 occupation=Sales
-0.5698736289837888 0.3153781642242884 occupation=Exec-managerial
-0.4280889210254435 0.28091511437065775 occupation=Prof-specialty
0.7990268016379739 -0.12394262743125586 occupation=Handlers-cleaners
-0.27306729836485216 -0.7285130044424423 occupation=Machine-op-inspct
0.8772033637099603 -0.717302513428776 occupation=Adm-clerical
-0.5546613574161496 0.8406014266613091 occupation=Farming-fishing
1.0445879798601867 0.4836875286743738 occupation=Transport-moving
-0.9172918197105598 -0.9813327707995381 occupation=Priv-house-serv
0.012757068763164436 0.07316847680908879 occupation=Protective-serv
-0.2093953677117801 -0.9280725130007696 occupation=Armed-Forces
0.5344846422175845 0.2883110181415103 relationship=Wife
-0.5728358994158951 0.3246627245081811 relationship=Own-child
0.20679359086304003 0.32312936276256593 relationship=Husband
0.05048845526294791 -0.970253656017345 relationship=Not-in-family
-0.5600683649163917 0.11541353565295169 relationship=Other-relative
-0.5091484680914132 -0.5002468152967361 relationship=Unmarried
0.6474261349276778 0.24832436923240886 race=White
-0.5836594320441058 -0.04582958186103586 race=Asian-Pac-Islander
-0.4221172930535959 -0.059273252244975705 race=Amer-Indian-Eskimo
-0.6225379466052227 -0.8631733153450961 race=Other
-0.7585995676376497 0.03464671969817112 race=Black
0.47398668348107537 0.4748870215057964 sex
0.49092340388965755 0.015310285230528525 capital-gain
0.6650320836783316 -0.8399283459535325 capital-loss
0.8975844848212118 0.6287300972185708 hours-per-week
0.2253218184580757 -1.1637211116816122 native-country=United-States
0.4155737407427937 -0.7999423123140288 native-country=Cambodia
0.12405676146401305 0.059424033176374 native-country=England
0.22992755340371593 -0.5008228616688709 native-country=Puerto-Rico
-0.24222260747699495 -0.361124631019752 native-country=Canada
0.2086483854733724 -0.6198689645141358 native-country=Germany
-0.33230511632669185 -0.7171615354269771 native-country=Outlying-US(Guam-USVI-etc)
0.37385380376124805 -0.939134738040786 native-country=India
1.009895678144962 0.09035050599533509 native-country=Japan
-0.8281674118426922 0.0117486706547634 native-country=Greece
0.9374706153145514 -0.7682998851540646 native-country=South
-0.43478756718831096 -0.18502856188182457 native-country=China
0.12359016411060746 -0.9204516377801106 native-country=Cuba
-0.1747299122178561 0.5579938112104574 native-country=Iran
-0.6235125223369671 -0.6045016410457078 native-country=Honduras
0.9463303938404596 0.04015376199904755 native-country=Philippines
-0.38805939211093654 0.08956267537593098 native-country=Italy
-0.5623282764521549 0.31307112881975246 native-country=Poland
0.0205856102774062 -0.5593122343141056 native-country=Jamaica
-0.17894056123096294 -0.6017893739782878 native-country=Vietnam
0.21558489720093538 0.365687437694054 native-country=Mexico
0.6328164600485774 -0.7874137471122998 native-country=Portugal
-0.7695936128635797 -0.8549310805911592 native-country=Ireland
0.925660695777108 -0.3455637214705114 native-country=France
0.36650487560283457 -0.236305323689082 native-country=Dominican-Republic
-0.20992710426398847 -0.039053797156845 native-country=Laos
-0.2898620318836659 -0.4342784923016628 native-country=Ecuador
0.740042676802536 -0.11356515279703865 native-country=Taiwan
-0.7233647034207519 -1.0422993446944162 native-country=Haiti
0.41481903313583174 -0.8627125939491253 native-country=Columbia
0.0196813518655591 0.22072249641443328 native-country=Hungary
-0.0883209012096392 0.8912844681859924 native-country=Guatemala
0.08220300605625444 -0.4911606503854674 native-country=Nicaragua
0.38377159093114305 0.5840590957927654 native-country=Scotland
-0.8862437658873331 -0.03268889744218385 native-country=Thailand
-0.2953642582413551 0.8366390059612379 native-country=Yugoslavia
0.047915262673014866 -0.7331851815933975 native-country=El-Salvador
-0.5716391614119049 -0.4778265216155576 native-country=Trinadad&Tobago
0.019726168238974138 -1.010492638934826 native-country=Peru
-0.41984536241692977 -0.07252678260187961 native-country=Hong
0.6686791110966271 -0.033816944385707 native-country=Holand-Netherlands
Hidden Weights:
-0.5368046123972788 0.3139324248336243
1.6006253796928451 -1.4225603971223253
>50K <=50K
Error sum for iteration 200 = 66.6795326039972
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.7155062913985143 0.10504646014782225 age
0.7675986255999572 -0.8755419413990346 workclass=Private
-0.08214510672921956 0.4319414813454575 workclass=Self-emp-not-inc
0.5201362492156613 0.5939700632077775 workclass=Self-emp-inc
-0.3869977412159066 0.24314178865595934 workclass=Federal-gov
1.0274643522179538 -0.009829290348602311 workclass=Local-gov
0.3354914353498638 0.4791156376432153 workclass=State-gov
-0.1440985789153221 0.5149800304573665 workclass=Without-pay
0.9895423792050526 0.3916761424690109 workclass=Never-worked
0.5916274248346431 0.37097988426057066 fnlwgt
0.7768546510295748 0.5744853965856724 education=Bachelors
-0.565673543174912 -0.18567133149087978 education=Some-college
0.9355996620026368 0.11197821111815755 education=11th
0.09530193698134597 -0.6571544950650732 education=HS-grad
0.9182223792285283 1.0389033986839027 education=Prof-school
0.8136113059061805 -0.4295997862146351 education=Assoc-acdm
0.37613195563663454 -0.27098533824743853 education=Assoc-voc
0.05379750047606305 0.20571406571146988 education=9th
-0.3010485895260366 0.34419358707154674 education=7th-8th
-0.10633789968292533 0.7415751876837167 education=12th
0.46181446568982415 0.31442435798177143 education=Masters
0.024568036947706078 -0.6474690215070807 education=1st-4th
-0.7836840082555616 -0.558751026856923 education=10th
0.022514171294465132 0.5059436314083149 education=Doctorate
0.6133686414618295 -0.21881235557187756 education=5th-6th
0.6705710621136876 -0.5160986451502492 education=Preschool
1.0172125890589991 1.4795876199758908 education-num
0.26686441963527296 1.6651921804410703 marital-status=Married-civ-spouse
0.5762455127138745 0.011469965103571173 marital-status=Divorced
0.9914763091536902 -1.8108348342825618 marital-status=Never-married
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0.8191113667071156 -0.2276974863430004 marital-status=Widowed
0.5170135209053568 -0.6935563256132398 marital-status=Married-spouse-absent
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0.8134237734592307 -0.42996138411029355 occupation=Handlers-cleaners
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0.8916864042606861 -0.5977146341451968 occupation=Adm-clerical
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1.064874062992372 -0.24122068280430792 occupation=Transport-moving
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0.021761224532112218 0.08241958665617212 occupation=Protective-serv
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0.5442217455675337 0.5450254650431565 relationship=Wife
-0.5303622153012003 -0.08542943638520778 relationship=Own-child
0.2060680400207118 0.3410570244730226 relationship=Husband
0.06216835510436403 -0.8368116288396822 relationship=Not-in-family
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-0.6063232654927718 -0.9619956151338194 race=Other
-0.7115706361943568 -0.17433956910652718 race=Black
0.5078248620644588 0.16064512631177275 sex
0.4980763371591231 -4.7474293281696213E-4 capital-gain
0.6680474600187427 -0.6586857672677333 capital-loss
0.8974652778542627 0.7546187001563572 hours-per-week
0.30058301080760974 -0.9985653932554522 native-country=United-States
0.41546376633259835 -0.7994054463064446 native-country=Cambodia
0.1334462598848693 0.005604640717337923 native-country=England
0.24063878463282357 -0.6057719475232463 native-country=Puerto-Rico
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0.2176786195238505 -0.6656537666396284 native-country=Germany
-0.3241198490329676 -0.7491020195572172 native-country=Outlying-US(Guam-USVI-etc)
0.3788740784253275 -0.9536076581763583 native-country=India
1.0180809454386803 0.05841002186509525 native-country=Japan
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0.9420500667021678 -0.7299318580910426 native-country=South
-0.4266022998945867 -0.21696904601206532 native-country=China
0.13585627695344293 -1.050366341718252 native-country=Cuba
-0.17078159907135484 0.5359251525444639 native-country=Iran
-0.6164166543996535 -0.6046111483064254 native-country=Honduras
0.9557357262956574 -0.016190695697547542 native-country=Philippines
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0.030172767582507688 -0.5937215295286241 native-country=Jamaica
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0.23238046516543306 0.1373373098149397 native-country=Mexico
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0.9346050696409657 -0.3895563368351411 native-country=France
0.37471839493544973 -0.26939177224611155 native-country=Dominican-Republic
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0.02786661915928165 0.18878201228419253 native-country=Hungary
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0.05637501233533781 -0.7671959193123842 native-country=El-Salvador
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0.027911435532696687 -1.0424331230650903 native-country=Peru
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0.6768643783903534 -0.06575742851594935 native-country=Holand-Netherlands
Hidden Weights:
-0.6070577874388073 0.4277486515428099
2.5058511590628227 -2.4713013908407286
>50K <=50K
Error sum for iteration 300 = 66.13354966709049
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.718456445081006 0.17983636896243554 age
0.7950976179017952 -0.5504041814943269 workclass=Private
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1.0312966723470733 -0.1981739527943355 workclass=Local-gov
0.35079907308763814 0.2686369776454384 workclass=State-gov
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0.6753396849127294 -0.5348378240543787 education=Preschool
1.0286106886435016 1.7947867516255331 education-num
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0.5020126964748873 0.00856776655253209 capital-gain
0.6678356508970532 -0.3659423524286005 capital-loss
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Hidden Weights:
-0.6695119116669687 0.4988517896918805
3.094286007454257 -3.084337478811324
>50K <=50K
Error sum for iteration 400 = 66.61406698527706
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.7172515434589463 0.28519982729633525 age
0.8180701213550682 -0.4534172648300898 workclass=Private
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Hidden Weights:
-0.7199421071748021 0.55195757694601
3.5551605087293234 -3.5509164931097192
>50K <=50K
Error sum for iteration 500 = 67.71364682133877
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.7142723365321215 0.4391223360669611 age
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0.5242226152208755 -0.008675486194017847 sex
0.5056391793222949 0.04165496558347135 capital-gain
0.6640820723275993 0.34990697579329333 capital-loss
0.8925248575499851 1.0255587770514492 hours-per-week
0.4033068572142217 -0.4827884247641104 native-country=United-States
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0.6862298977979212 -0.11281018257649711 native-country=Holand-Netherlands
Hidden Weights:
-0.7380578109957695 0.5713476238843359
3.9670338102723672 -3.9645296209231766
>50K <=50K
Error sum for iteration 600 = 68.49250491004963
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.7109602279559492 0.6054141280797803 age
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Hidden Weights:
-0.7583001708857922 0.5923652614593932
4.340091848449468 -4.3381667721207045
>50K <=50K
Error sum for iteration 700 = 68.86848996198064
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.7081488922890493 0.7263546904584726 age
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Hidden Weights:
-0.7791343175694868 0.6137658538565962
4.660522008545186 -4.6588017050614035
>50K <=50K
Error sum for iteration 800 = 68.95073037520018
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.7058925458757364 0.7892013677570769 age
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0.6817082418273264 -0.5856147175937824 education=Preschool
1.0351826315157722 2.1200315891972945 education-num
0.32179836319365235 1.336386387794624 marital-status=Married-civ-spouse
0.5972563404260258 -0.2952201593237934 marital-status=Divorced
1.0145433826474797 -0.9142036435054096 marital-status=Never-married
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0.8398952839389894 -1.0145391985430066 marital-status=Widowed
0.5334645702173673 -0.9547679276669477 marital-status=Married-spouse-absent
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1.0859568801687691 -1.4893971255948588 occupation=Transport-moving
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0.75119593487718 -0.006376210925754378 race=White
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0.5216692300490916 -0.01845288895492323 sex
0.5064192596944657 0.11198867338210293 capital-gain
0.6577827820783696 1.478018014469592 capital-loss
0.8785442663247107 0.9103676793127532 hours-per-week
0.44643444414788924 -0.4850983849665203 native-country=United-States
0.3670486123931888 0.19636370330857308 native-country=Cambodia
0.15316914693503156 -0.31315832172984076 native-country=England
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0.23035402640997202 -0.7795144293877918 native-country=Germany
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0.37778302144500797 -0.5737559287816462 native-country=India
1.0291801113743975 -0.010868615756826645 native-country=Japan
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0.9403481141844936 -0.13672969077302718 native-country=South
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0.16166433173408357 -1.9854737373327997 native-country=Cuba
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0.9729145712890952 -0.4070010951059087 native-country=Philippines
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0.04250867890389767 -0.6648080651330902 native-country=Jamaica
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0.24241159141297958 0.32015693495405323 native-country=Mexico
0.6616736101256576 -1.4983657551034626 native-country=Portugal
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0.9462604726168908 -0.4674031878393903 native-country=France
0.3858328286045575 -0.33929659438498255 native-country=Dominican-Republic
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0.43422860875168684 -0.9838159130206942 native-country=Columbia
0.038965785095043004 0.11950337466226922 native-country=Hungary
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0.4030560241606395 0.4828399740406089 native-country=Scotland
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0.0675051807643683 -0.8366565787764821 native-country=El-Salvador
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0.0390106014684581 -1.1117117606870297 native-country=Peru
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Hidden Weights:
-0.7952822676572967 0.6303776040086306
4.929717600256814 -4.928076014384027
>50K <=50K
Error sum for iteration 900 = 68.85023051857982
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.7040250042448047 0.8118015204089692 age
0.880957131835883 -0.3343711021522213 workclass=Private
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0.5115584625089725 0.602857578002084 workclass=Self-emp-inc
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1.0223777995255456 -0.13964574495986842 workclass=Local-gov
0.38996253471999026 -0.2921383866084981 workclass=State-gov
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1.0006323619782058 0.31811760840854625 workclass=Never-worked
0.5946437931907337 0.3569983503588278 fnlwgt
0.7608974086645882 -0.32399157382238947 education=Bachelors
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0.9230926949691514 2.1534744395981127 education=Prof-school
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0.4875693058783143 -0.9015112798063694 education=Masters
0.040133278976215166 -0.9377470039265515 education=1st-4th
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0.32425973280977777 1.3560558138271952 marital-status=Married-civ-spouse
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0.506089096978691 0.13963674524317254 capital-gain
0.6565321868539957 1.756653076426217 capital-loss
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0.06746583744404117 -0.8408820809847952 native-country=El-Salvador
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0.039001418305884515 -1.1159916571255708 native-country=Peru
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0.6879543611635215 -0.13931596257640586 native-country=Holand-Netherlands
Hidden Weights:
-0.8062121353825841 0.6417187223981073
5.156341366730178 -5.1547370875082645
>50K <=50K
Error sum for iteration 1000 = 68.58738628509465
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.7024535163485879 0.8146439655722382 age
0.8884068613575489 -0.32636318887044524 workclass=Private
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1.000483511312976 0.3144679604481026 workclass=Never-worked
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0.04037241058046458 -0.9665105010808115 education=1st-4th
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0.011230621513698445 1.4425079536274539 education=Doctorate
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0.6815421490226551 -0.5933100493294827 education=Preschool
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0.32633339994196414 1.3836065798986135 marital-status=Married-civ-spouse
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0.5055993862135538 0.16921248129230285 capital-gain
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0.2416743442808428 0.40224187482673296 native-country=Mexico
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0.9461422830430057 -0.4760167282142206 native-country=France
0.38567067245872105 -0.346891531617646 native-country=Dominican-Republic
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0.7516872829437508 -0.03246268794043763 native-country=Taiwan
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0.4340960385619121 -0.9981673605749438 native-country=Columbia
0.03880775126725232 0.11157383026327902 native-country=Hungary
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0.40289799033285434 0.4749104296416224 native-country=Scotland
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0.06728445897052983 -0.8444812503982233 native-country=El-Salvador
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0.03885256764066741 -1.119641305086004 native-country=Peru
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0.6878055104983083 -0.14296561053685578 native-country=Holand-Netherlands
Hidden Weights:
-0.8124239317527014 0.6483206542047669
5.3487793236739885 -5.3472083081573905
>50K <=50K
Error sum for iteration 1100 = 68.20081593696848
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.7011125504600538 0.8113254780429159 age
0.8947984309616318 -0.3218993492017356 workclass=Private
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0.39794446772148784 -0.3258767510460261 workclass=State-gov
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1.0002541676571763 0.3111308775041189 workclass=Never-worked
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0.5199769774749124 -0.14574016830449585 sex
0.5050121177621475 0.19982433263550822 capital-gain
0.6552104188194906 2.1623034291610854 capital-loss
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Hidden Weights:
-0.8146213180996075 0.6509019461615752
5.512932281240854 -5.511402230763868
>50K <=50K
Error sum for iteration 1200 = 67.75239955152529
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.6999372741633985 0.8081955456955504 age
0.9003065869607102 -0.3204409197300981 workclass=Private
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Hidden Weights:
-0.8138579887922504 0.650519571424736
5.653224817249967 -5.651739700632385
>50K <=50K
Error sum for iteration 1300 = 67.28763371449739
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
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0.04125204733437101 -0.6818508413329649 native-country=Jamaica
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0.2408432133752344 0.4891204578158093 native-country=Mexico
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0.9453691762600598 -0.48651123729451917 native-country=France
0.38483170966931135 -0.35579168341109196 native-country=Dominican-Republic
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0.7499701127849161 0.025090027759724062 native-country=Taiwan
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0.43329845868836636 -1.0155746645977708 native-country=Columbia
0.03797704302238278 0.10208202335021911 native-country=Hungary
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0.4020672820879785 0.4654186227285681 native-country=Scotland
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0.06635232218732719 -0.8538557862450388 native-country=El-Salvador
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0.03802185939579787 -1.1291331119990706 native-country=Peru
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0.6869748022534037 -0.1524574174499207 native-country=Holand-Netherlands
Hidden Weights:
-0.8112048746154966 0.6482444865214989
5.773506510246036 -5.7720631643376095
>50K <=50K
Error sum for iteration 1400 = 66.83042309360549
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.69789063982196 0.8083340846330284 age
0.9093170346494844 -0.3234977465032001 workclass=Private
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1.0136238016169068 -0.11938341579970356 workclass=Local-gov
0.4089560882405857 -0.3672509652949574 workclass=State-gov
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0.9992985032393495 0.3020960284144352 workclass=Never-worked
0.5896136414695824 0.26031118175797174 fnlwgt
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0.680335713092298 -0.6050901356635354 education=Preschool
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0.3332619903854294 1.5401241341321703 marital-status=Married-civ-spouse
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0.5212125115975242 -0.2855266977193454 sex
0.5029378798429412 0.2903815803531718 capital-gain
0.6550509915975988 2.530912112489343 capital-loss
0.839376451356173 0.6940337065323523 hours-per-week
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0.03766755956707008 -1.13201323711965 native-country=Peru
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Hidden Weights:
-0.8075020553090644 0.6449170801403317
5.877164820849401 -5.875755058476066
>50K <=50K
Error sum for iteration 1500 = 66.39489982323845
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.6969501806269269 0.8111198878276749 age
0.9130746055535537 -0.3267807261939644 workclass=Private
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Hidden Weights:
-0.8033370303499647 0.6411259491205817
5.967061774440504 -5.965675159216815
>50K <=50K
Error sum for iteration 1600 = 65.9842759038721
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.6960288996769066 0.8149449343888762 age
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0.5226763513473235 -0.360377679314332 sex
0.5013787115352717 0.34601255812543286 capital-gain
0.6555484300785968 2.690555517748463 capital-loss
0.8247353420852327 0.6603944950677203 hours-per-week
0.4721919992266671 -0.5865126893792897 native-country=United-States
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Hidden Weights:
-0.7991019075398489 0.6372648760622954
6.045540798239849 -6.044166633079038
>50K <=50K
Error sum for iteration 1700 = 65.5980692748371
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.6951038591124389 0.8193117348029608 age
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Hidden Weights:
-0.7950539024152572 0.6335931031728468
6.114492020783011 -6.113120464859273
>50K <=50K
Error sum for iteration 1800 = 65.24143661471841
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.6941539451725888 0.8238508975127157 age
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Hidden Weights:
-0.7913621014949762 0.6302819744077605
6.175434127555423 -6.174056686869893
>50K <=50K
Error sum for iteration 1900 = 64.91007252872613
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.6931590231281759 0.8283074025956239 age
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0.6779737854311758 -0.6173680638407026 education=Preschool
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0.3383060721398834 1.764556466728708 marital-status=Married-civ-spouse
0.544213789748331 -0.23549528009431497 marital-status=Divorced
1.0082216926054663 -0.8879852588495032 marital-status=Never-married
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1.0830589005468683 -1.635494241772705 occupation=Transport-moving
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0.7645662678886769 0.16246607760179593 race=White
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0.5246193885137328 -0.44499297160906354 sex
0.49873052079343083 0.42087580661505525 capital-gain
0.6566504152963871 2.862670746709951 capital-loss
0.80045060769024 0.6316915003302027 hours-per-week
0.4633938069010438 -0.5886558151597157 native-country=United-States
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0.9285673372712071 0.42953512508296987 native-country=South
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0.16414708864737623 -2.4889148599159916 native-country=Cuba
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0.9428349008824396 -0.5047165216041156 native-country=France
0.38211769792669414 -0.3705063247096703 native-country=Dominican-Republic
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0.06347116332984133 -0.8693540240239281 native-country=El-Salvador
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0.035324504408624086 -1.1447458021927523 native-country=Peru
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Hidden Weights:
-0.7881407424627012 0.6274481871172897
6.229590492782589 -6.228200132316859
>50K <=50K
Error sum for iteration 2000 = 64.60340406494556
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.6920991939565162 0.8325163592080604 age
0.9272131044901419 -0.34882320119147303 workclass=Private
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0.5001499268533064 0.5426437475799618 workclass=Self-emp-inc
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1.0063196047784235 -0.1165121273562118 workclass=Local-gov
0.42851438674054954 -0.4316442763201549 workclass=State-gov
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0.9963353597328665 0.2871195400174981 workclass=Never-worked
0.5834763160354816 0.12360270353029429 fnlwgt
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0.4977346425607823 0.44369785464084577 capital-gain
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Hidden Weights:
-0.7854724257742538 0.6251770413470017
6.277952415312692 -6.27654347083996
>50K <=50K
Error sum for iteration 2100 = 64.32074828757901
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.6909540852916068 0.8363799806383823 age
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0.49666418236088594 0.46555121962970863 capital-gain
0.6574426625121337 2.9498239705685863 capital-loss
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0.06210759582774574 -0.8737344760985958 native-country=El-Salvador
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0.03401484920357032 -1.149145005502437 native-country=Peru
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0.6829677920611884 -0.17246931095335133 native-country=Holand-Netherlands
Hidden Weights:
-0.7834245273848822 0.6235389404284551
6.321329103044307 -6.319897104029666
>50K <=50K
Error sum for iteration 2200 = 64.06084555926128
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.6897021485810674 0.839849023323717 age
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0.5253444684762911 -0.5061655477667268 sex
0.49550511485806537 0.4864945727072998 capital-gain
0.6578222956033617 2.9877347803631706 capital-loss
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0.4465008999792988 -0.5828600857040241 native-country=United-States
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Hidden Weights:
-0.7820614113001381 0.6226017384998066
6.360386334057423 -6.358927801850828
>50K <=50K
Error sum for iteration 2300 = 63.82348760525532
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.688319961160379 0.8429088669608447 age
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Hidden Weights:
-0.781454462836389 0.6224409653050348
6.395676116078582 -6.3941883722592845
>50K <=50K
Error sum for iteration 2400 = 63.6079327375262
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
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0.0342405539995188 -0.7074569191829483 native-country=Jamaica
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0.23880658898338405 0.6906604362857341 native-country=Mexico
0.6554205955845768 -2.019357152698263 native-country=Portugal
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0.9390966277583604 -0.5174197676006802 native-country=France
0.37818193094063945 -0.38044538473852374 native-country=Dominican-Republic
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0.7410998586395143 0.17806715915940677 native-country=Taiwan
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0.4267843084579133 -1.060674677266664 native-country=Columbia
0.031356485141284446 0.07607683208791058 native-country=Hungary
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0.09387813933196919 -0.6358063147119895 native-country=Nicaragua
0.3954467242068936 0.43941343146623274 native-country=Scotland
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0.05941767581418174 -0.8797086007837398 native-country=El-Salvador
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0.03140130151469954 -1.1551383032612903 native-country=Peru
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0.680354244372324 -0.17846260871223474 native-country=Holand-Netherlands
Hidden Weights:
-0.7816916069928245 0.6231496163557891
6.427659411062292 -6.426140414314323
>50K <=50K
Error sum for iteration 2500 = 63.41413575011254
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.6850580127182806 0.8478584766741519 age
0.9356254164191848 -0.37097735772582247 workclass=Private
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0.493204939758491 0.5308037783540713 workclass=Self-emp-inc
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1.0008359578935715 -0.12229029673757771 workclass=Local-gov
0.44207433071050295 -0.4704992218760838 workclass=State-gov
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0.9919216379866361 0.2771109597179612 workclass=Never-worked
0.5752923499982626 0.03647729075096683 fnlwgt
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0.6729326988183076 -0.6294802287706858 education=Preschool
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0.3358423732506133 2.0178330449852506 marital-status=Married-civ-spouse
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0.5238166661309851 -0.552416766493945 sex
0.49130726531521274 0.5443957625865737 capital-gain
0.658774282141438 3.084990911542912 capital-loss
0.7363754668283131 0.6066418512936679 hours-per-week
0.41941467693317536 -0.5731649968254835 native-country=United-States
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Hidden Weights:
-0.7828878649738493 0.6248491058514156
6.456723587039992 -6.455171808942437
>50K <=50K
Error sum for iteration 2600 = 63.2426328298279
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.6831172881478197 0.8498163829610361 age
0.9365390549313131 -0.37496647230843494 workclass=Private
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0.9906516681697913 0.2753100675840235 workclass=Never-worked
0.5729700208928559 0.022489493208517043 fnlwgt
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0.4895812431893915 0.5622082312634366 capital-gain
0.6589931260557123 3.113118764431795 capital-loss
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Hidden Weights:
-0.7851986412684311 0.6277031550330768
6.483195882530087 -6.481610230024326
>50K <=50K
Error sum for iteration 2700 = 63.094606935732926
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.6809255701028163 0.8514940044848427 age
0.9371057226759256 -0.3787330966905957 workclass=Private
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0.5207678479933745 -0.5775969394075784 sex
0.4876316618368634 0.5793430610685201 capital-gain
0.6591424909727545 3.139557787756659 capital-loss
0.7064191423986846 0.6023514723260092 hours-per-week
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Hidden Weights:
-0.7888378110347856 0.6319368353336369
6.507353875714596 -6.5057336684603095
>50K <=50K
Error sum for iteration 2800 = 62.972712667885666
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.67845125227393 0.8529514481373032 age
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Hidden Weights:
-0.7941031708341235 0.6378636227932113
6.529433765128132 -6.527778776792149
>50K <=50K
Error sum for iteration 2900 = 62.881742312057106
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.6756754854699681 0.8542592566697003 age
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Hidden Weights:
-0.8014118727030405 0.6459236914979005
6.549637232553456 -6.54794780109644
>50K <=50K
Error sum for iteration 3000 = 62.82932882504643
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.6726167223854941 0.8555024532734558 age
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0.319501025932673 2.2074705836242883 marital-status=Married-civ-spouse
0.41974915715679845 -0.3179829357276336 marital-status=Divorced
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0.5108474564368356 -0.6091437281413902 sex
0.47987937696647553 0.6269932779562792 capital-gain
0.6590636875662631 3.210780252101126 capital-loss
0.6450268545581701 0.5980607052883586 hours-per-week
0.3348088579296747 -0.5536264728853688 native-country=United-States
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0.9295781502623753 -0.5302611366080047 native-country=France
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Hidden Weights:
-0.8113461944303296 0.6567351108665169
6.568137880892176 -6.566415074135904
>50K <=50K
Error sum for iteration 3100 = 62.82713959435609
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
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0.4764199551798279 0.6417073527984414 capital-gain
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Hidden Weights:
-0.8247002676474089 0.6711513982398041
6.585088948359471 -6.583334729491935
>50K <=50K
Error sum for iteration 3200 = 62.89093009698298
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
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0.6647089433917234 -0.19206481655064936 native-country=Holand-Netherlands
Hidden Weights:
-0.8424916900437677 0.6902948548967905
6.600635472063711 -6.598852794922491
>50K <=50K
Error sum for iteration 3300 = 63.04042754832475
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.6639120924470686 0.8601608378414882 age
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Hidden Weights:
-0.8658578122305484 0.7154926453382761
6.614935898857497 -6.613128941175718
>50K <=50K
Error sum for iteration 3400 = 63.29364048845334
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.6633872385544171 0.8628012041911628 age
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Hidden Weights:
-0.8957585607870818 0.7480340105695656
6.628197217129349 -6.6263729103846245
>50K <=50K
Error sum for iteration 3500 = 63.65804307555337
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
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0.22512675309371744 0.8399253496428306 native-country=Mexico
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0.9132506347128936 -0.5399820888267886 native-country=France
0.351494692777923 -0.39828792883730035 native-country=Dominican-Republic
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0.7110383425817681 0.28840798564599796 native-country=Taiwan
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0.004723889611998407 0.057571496896643065 native-country=Hungary
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0.03241164854019553 -0.8981829662828426 native-country=El-Salvador
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0.004768705985413646 -1.1736436384526372 native-country=Peru
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0.6537216488430904 -0.1969679439034992 native-country=Holand-Netherlands
Hidden Weights:
-0.932597847083518 0.788818238991236
6.640718479893952 -6.638890730469933
>50K <=50K
Error sum for iteration 3600 = 64.12227345392625
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.6735887383438924 0.8724490917535555 age
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1.0030732680340646 -0.1146113171758154 workclass=Local-gov
0.4241433309932461 -0.5297485274515427 workclass=State-gov
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0.4437122879983475 -0.6501450388432004 sex
0.45151513904235396 0.7071784603256203 capital-gain
0.6624480493891399 3.333913820197623 capital-loss
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Hidden Weights:
-0.976139926886772 0.838192546191271
6.65292330893984 -6.651116000118904
>50K <=50K
Error sum for iteration 3700 = 64.65318109082203
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.6866540264963492 0.8807697729008204 age
0.9125287042764704 -0.3722083208862307 workclass=Private
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Hidden Weights:
-1.0258921116536437 0.8961302370652037
6.665358766310043 -6.663594759702081
>50K <=50K
Error sum for iteration 3800 = 65.19960070689226
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.7054757854782807 0.8921343955618943 age
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0.39778237656599696 -0.6550044625980216 sex
0.44015020316060594 0.7299825330861889 capital-gain
0.6711044767374408 3.3758408268401934 capital-loss
0.2700441654863997 0.5814286241492745 hours-per-week
0.050536007653885585 -0.545087925307051 native-country=United-States
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Hidden Weights:
-1.0816088868792457 0.9624946445942861
6.67864578838953 -6.676915268872441
>50K <=50K
Error sum for iteration 3900 = 65.70569044678042
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.7294268739450449 0.9066030581159815 age
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Hidden Weights:
-1.1435801262881018 1.0371853109611384
6.693380679683031 -6.691609141058841
>50K <=50K
Error sum for iteration 4000 = 66.13137672455109
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.7573967115156381 0.9237083264402239 age
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Hidden Weights:
-1.212658100594437 1.1202287281884453
6.710029603416299 -6.708080072054816
>50K <=50K
Error sum for iteration 4100 = 66.46508325303645
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.7881894973876767 0.9426465281771464 age
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0.6378187312648835 -0.6556174395204277 education=Preschool
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0.22400627764150774 2.550560038548668 marital-status=Married-civ-spouse
0.34186714722729106 -0.4406063279545478 marital-status=Divorced
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1.0341871388102972 -1.7228654356072535 occupation=Transport-moving
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0.5350958199645794 0.35842780923150097 race=White
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0.3173303757159323 -0.6586857853435816 sex
0.42422802359210127 0.7610441206838948 capital-gain
0.6937063765235173 3.4402014969842902 capital-loss
0.07149455703190158 0.5519321130997046 hours-per-week
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0.15725573456343356 -2.903213734418301 native-country=Cuba
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Hidden Weights:
-1.2900286913807884 1.2118157363267428
6.728890126931112 -6.72660592417289
>50K <=50K
Error sum for iteration 4200 = 66.7146245450549
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.8208142615339998 0.9626351681036152 age
0.9865206958729914 -0.31828219799735974 workclass=Private
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1.1688300156970337 -0.023012054584074154 workclass=Local-gov
0.24187958798302256 -0.5727951778446247 workclass=State-gov
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0.4190063446173457 0.7702695748111232 capital-gain
0.7029636449140079 3.460670953564235 capital-loss
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0.023522965419564446 -0.9097314491674956 native-country=El-Salvador
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0.6460120443354169 -0.20853015448486553 native-country=Holand-Netherlands
Hidden Weights:
-1.3767797252474412 1.3121697472156255
6.75013474281396 -6.747391447338238
>50K <=50K
Error sum for iteration 4300 = 66.89067066357838
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.8545866729792967 0.9831572861848471 age
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0.025393158159753907 -0.9111453356535029 native-country=El-Salvador
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-0.4403552495223796 -0.24865591670487547 native-country=Hong
0.6481692239912233 -0.209946078488703 native-country=Holand-Netherlands
Hidden Weights:
-1.47345273995384 1.421252703983917
6.773867669390985 -6.770605071544606
>50K <=50K
Error sum for iteration 4400 = 67.00108850387946
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.8891100352149404 1.0039925991892218 age
1.0427523307981392 -0.29515345912745355 workclass=Private
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0.5683273090507303 0.5735936947169552 workclass=Self-emp-inc
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1.2618023137213947 0.016631727135808176 workclass=Local-gov
0.15685487833993705 -0.6014411272008302 workclass=State-gov
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0.9634985840714961 0.24613595003715563 workclass=Never-worked
0.4297154653614804 -0.05687632025134846 fnlwgt
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0.020406321700507764 -1.4475528697417028 education=1st-4th
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0.6436687354133137 -0.6592486267248294 education=Preschool
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0.23955287715040283 -0.6663194859252562 sex
0.40760827623951507 0.7861931465598955 capital-gain
0.7224657963978833 3.498680652123461 capital-loss
-0.14588613013535887 0.5063601510508432 hours-per-week
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0.027738927380936567 -0.9124948591000711 native-country=El-Salvador
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0.0018676403991287449 -1.187973315496909 native-country=Peru
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0.6508205832568162 -0.21129762094780227 native-country=Holand-Netherlands
Hidden Weights:
-1.5797340531357484 1.538446864740122
6.800133365476515 -6.796363989459864
>50K <=50K
Error sum for iteration 4500 = 67.04649278686685
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.9242137409367368 1.0251291400880063 age
1.068800023753587 -0.28443569378692135 workclass=Private
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0.024065418054566714 -1.4546533201759577 education=1st-4th
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0.4010454447393837 0.7925797123571078 capital-gain
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Hidden Weights:
-1.6943162723097482 1.6623351078587214
6.828874148144161 -6.8246776708529175
>50K <=50K
Error sum for iteration 4600 = 67.0237261822647
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.959881404115967 1.0466630019371705 age
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0.28149076233656567 0.9323292904630476 native-country=India
0.9983718443082882 -0.08963909292751251 native-country=Japan
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0.8681122931523733 0.9799696524385197 native-country=South
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0.2023446829884056 -2.9732358900482048 native-country=Cuba
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0.9698188569508595 -0.9456710662458011 native-country=Philippines
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0.2616570306620855 0.9577815074495621 native-country=Mexico
0.6453189411749541 -2.3792702340657472 native-country=Portugal
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0.9176647969694328 -0.5579760498463568 native-country=France
0.35396323977868155 -0.41368502554191555 native-country=Dominican-Republic
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0.6958037321759057 0.3870844896102491 native-country=Taiwan
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0.008157518028907098 0.04073289749159014 native-country=Hungary
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0.03343058386109376 -0.9149998221910138 native-country=El-Salvador
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0.008202334402322355 -1.1904822378576563 native-country=Peru
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0.6571552772600141 -0.21380654330855253 native-country=Holand-Netherlands
Hidden Weights:
-1.8149348487292751 1.7906622204029932
6.859870772178485 -6.8553807140118765
>50K <=50K
Error sum for iteration 4700 = 66.9282884281777
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
0.9961730727668692 1.0687283965285228 age
1.1064533609580902 -0.26717987091757966 workclass=Private
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0.6748517094162952 0.6148358114144992 workclass=Self-emp-inc
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1.412289835254782 0.07855032744594508 workclass=Local-gov
0.020706448058729513 -0.655845332235286 workclass=State-gov
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0.19667069018938646 -0.6775263138481922 sex
0.38549967424397485 0.8014179842587325 capital-gain
0.7510344993268688 3.5487603508257624 capital-loss
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Hidden Weights:
-1.9386165332831595 1.9205402557442492
6.892707610177094 -6.888091371744934
>50K <=50K
Error sum for iteration 4800 = 66.75761341387972
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
1.03314437559169 1.0914531758665647 age
1.1150292567847504 -0.2614892856011823 workclass=Private
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Hidden Weights:
-2.0621470652940403 2.048897518135779
6.9267945783627995 -6.9222277816529205
>50K <=50K
Error sum for iteration 4900 = 66.51920616776924
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
1.0707769855842493 1.1149231646422815 age
1.115766500250593 -0.2580019203994432 workclass=Private
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0.788925191323165 -1.6401200219138308 occupation=Handlers-cleaners
-0.0011198123003029188 0.40745187109666137 occupation=Machine-op-inspct
1.3334499178894748 0.09256495435293215 occupation=Adm-clerical
-0.13813618913961945 0.10370260488553996 occupation=Farming-fishing
1.0172668270069494 -1.6343495589907577 occupation=Transport-moving
-0.9177383392177301 -1.164621191774877 occupation=Priv-house-serv
0.147006805839397 1.0378885744531827 occupation=Protective-serv
-0.21132644447748214 -1.1119718443072049 occupation=Armed-Forces
1.0630696560956912 -0.3549354501823865 relationship=Wife
-0.08946613538599206 -2.3959167492140794 relationship=Own-child
-0.27131957342407087 0.11382925211359561 relationship=Husband
0.027791378497227095 1.3005032715428304 relationship=Not-in-family
-0.4297578631510759 -0.11977989319314378 relationship=Other-relative
-1.1568547798128261 -1.5287221549709806 relationship=Unmarried
0.6065973820328789 0.41245787913463433 race=White
-0.7755619927520917 0.2791477055850367 race=Asian-Pac-Islander
-0.3113325975452928 -1.3240025353505325 race=Amer-Indian-Eskimo
-0.4191430493949602 -2.2997974878469667 race=Other
-0.845852600347039 -0.13586009472260144 race=Black
0.21084642997326286 -0.6832565646758291 sex
0.3663771150163337 0.8041847535795702 capital-gain
0.7688408817551174 3.579758147067842 capital-loss
-0.6160726092630777 0.4017663150404399 hours-per-week
1.908164003290846E-4 -0.6359454202594779 native-country=United-States
0.1439522706498783 2.930504236698296 native-country=Cambodia
0.218134021424099 -0.8734791404339642 native-country=England
0.2754585253442779 -2.8531529622189566 native-country=Puerto-Rico
-0.30299166901261826 1.2140463254032816 native-country=Canada
0.2463688268829197 -0.942104044185925 native-country=Germany
-0.33275163583390144 -0.9004499564023305 native-country=Outlying-US(Guam-USVI-etc)
0.285246969647082 0.9642411281561328 native-country=India
1.0094491586377439 -0.09293791498003602 native-country=Japan
-0.8286139313498624 -0.17153975032060356 native-country=Greece
0.8740434719937341 1.004493747395067 native-country=South
-0.43523408669552055 -0.36831698285718634 native-country=China
0.23772513299002335 -3.0136474555827086 native-country=Cuba
-0.1639315733220003 -0.0565088549026351 native-country=Iran
-0.6203308223852442 -0.7343784677272965 native-country=Honduras
0.9843044118931996 -0.9534420458862715 native-country=Philippines
-0.3919897260463215 -0.10286284897458114 native-country=Italy
-0.4927357741864139 -2.2157872274445256 native-country=Poland
0.024398837373455322 -0.7466084644633502 native-country=Jamaica
-0.17938708073821197 -0.7850777949536412 native-country=Vietnam
0.2754082077492184 0.9851819585285423 native-country=Mexico
0.6610651120044597 -2.41777863153822 native-country=Portugal
-0.77004013237075 -1.0382195015665683 native-country=Ireland
0.9280681634306416 -0.5607021445539295 native-country=France
0.36449892598266825 -0.4165068019699488 native-country=Dominican-Republic
-0.1300129017595869 -1.8470046858114875 native-country=Laos
-0.20404291980594932 -2.196839325835812 native-country=Ecuador
0.6983668362433711 0.4136046157442336 native-country=Taiwan
-0.648980708354605 -1.2272717737419239 native-country=Haiti
0.41481421736816176 -1.1098038625743796 native-country=Columbia
0.019234832358352102 0.037434075439067606 native-country=Hungary
-0.08876742071685276 0.707996047210639 native-country=Guatemala
0.0817564865490377 -0.6744490713608227 native-country=Nicaragua
0.38332507142393346 0.40077067481740886 native-country=Scotland
-0.8873261967838956 -0.3601146318666604 native-country=Thailand
-0.2958107777485647 0.6533505849858845 native-country=Yugoslavia
0.04356831307060162 -0.9182929565810154 native-country=El-Salvador
-0.5720856809190751 -0.661114942590918 native-country=Trinadad&Tobago
0.019279648731767424 -1.193781059910177 native-country=Peru
-0.42029188192413935 -0.25581520357724014 native-country=Hong
0.6682325915894569 -0.21710536536107186 native-country=Holand-Netherlands
Hidden Weights:
-2.182654154754563 2.1730489715910046
6.961451764798783 -6.957091814496488
>50K <=50K
Options: -I 5000
Back Propagation Neural Network:
Numer Input Nodes: 104
Number Hidden Nodes: 2
Number Output Nodes: 2
-I 5000
-E 0.01
-S 1627800787
-H 2
-M 0.01
Input Weights:
1.1085595610782564 1.138904816864027 age
1.1088991048452475 -0.2566250835791894 workclass=Private
-1.2833353630266318 -2.3882116657007946 workclass=Self-emp-not-inc
0.849143293560728 0.6666702651395426 workclass=Self-emp-inc
0.004755939411368433 1.2957686616507285 workclass=Federal-gov
1.561809376913061 0.13156007339284653 workclass=Local-gov
-0.12568597251861904 -0.7192043040872692 workclass=State-gov
-0.1488101100048841 0.3626343310081818 workclass=Without-pay
0.9848308481155356 0.23933044301982084 workclass=Never-worked
0.3954855818040808 -0.15060445323138694 fnlwgt
0.8067986880729305 -0.2671860704694165 education=Bachelors
-0.5806150371669325 -0.44661276734209054 education=Some-college
0.8842263554956706 -2.8115376121581543 education=11th
0.6762927673835895 -0.2087420285461525 education=HS-grad
0.8540248405346124 3.5089238255172948 education=Prof-school
1.6261572490421239 -0.11411221062093957 education=Assoc-acdm
-0.19733080571499773 0.28743265933378803 education=Assoc-voc
0.3778553676217305 -1.83813486875828 education=9th
-0.16916153406438408 1.1759020832615086 education=7th-8th
0.031737692306671964 3.7663268922178794 education=12th
-1.1217205958097152 -1.714376063611664 education=Masters
0.04454273739110473 -1.4876032245312307 education=1st-4th
-0.7039390268773704 -1.5829454834176684 education=10th
0.026719486672029582 0.9522995019230573 education=Doctorate
0.6731147175144697 -1.8588632685263378 education=5th-6th
0.6638320795790076 -0.66439231491228 education=Preschool
0.19153284379322716 3.2458142552201488 education-num
0.22438150172229246 2.746213068681565 marital-status=Married-civ-spouse
0.8026116758444306 -0.4172534775232062 marital-status=Divorced
0.2951360952853854 -1.2872516390712052 marital-status=Never-married
0.12468574078261703 -1.0574950031117922 marital-status=Separated
0.9547534628740922 -2.389906736168166 marital-status=Widowed
0.6461663348726455 -1.4360411305082175 marital-status=Married-spouse-absent
-0.20749635319130164 0.1751388858291761 marital-status=Married-AF-spouse
0.37605957618063157 0.28604871379093727 occupation=Tech-support
0.30899895754000295 0.308903491986923 occupation=Craft-repair
0.5362620007697871 0.41115423831781217 occupation=Other-service
-1.0822705497634395 -0.40884087670200897 occupation=Sales
-0.8025256480534183 1.0289165945631937 occupation=Exec-managerial
-2.7345569180012363 -0.7799512936064004 occupation=Prof-specialty
0.7892053725585707 -1.6420238606614008 occupation=Handlers-cleaners
0.02111816377912456 0.42037017115046404 occupation=Machine-op-inspct
1.346408298173041 0.08647513368287074 occupation=Adm-clerical
-0.08642369469439827 0.12152848799960674 occupation=Farming-fishing
1.0154998330404412 -1.6262247413672484 occupation=Transport-moving
-0.9138180835063313 -1.165618954378938 occupation=Priv-house-serv
0.1741159603092055 1.0494207265118052 occupation=Protective-serv
-0.20777237278175786 -1.1129570375390243 occupation=Armed-Forces
1.1231351656162343 -0.3350551853779573 relationship=Wife
-0.016655432232143483 -2.4058645705526227 relationship=Own-child
-0.32152834943415753 0.11660502361354896 relationship=Husband
0.03561183358335989 1.3172822417273233 relationship=Not-in-family
-0.43781928259511954 -0.14430821595463095 relationship=Other-relative
-1.184397672159514 -1.5476496938167221 relationship=Unmarried
0.632316724705822 0.41685593101133234 race=White
-0.7794081979276049 0.2828766830045435 race=Asian-Pac-Islander
-0.29760810217370925 -1.330704228247536 race=Amer-Indian-Eskimo
-0.4080415715751996 -2.3076817969171897 race=Other
-0.8415883867875074 -0.14237203590446101 race=Black
0.2323243605080835 -0.6850758196274039 sex
0.35558885303530297 0.80317297259775 capital-gain
0.777855272592058 3.595259620625185 capital-loss
-0.7216372230911166 0.3783913501192629 hours-per-week
0.0024791664541745574 -0.6453012063442589 native-country=United-States
0.14034112669064575 2.9529693405171455 native-country=Cambodia
0.22703221132805393 -0.8790682298290313 native-country=England
0.2806246746058275 -2.8646048315715276 native-country=Puerto-Rico
-0.3034707506239628 1.2330305338707905 native-country=Canada
0.2542083510638698 -0.944912331489415 native-country=Germany
-0.3288313801224919 -0.9014477190063943 native-country=Outlying-US(Guam-USVI-etc)
0.28702463422197033 0.9729582763984695 native-country=India
1.0133694143491594 -0.0939356775841034 native-country=Japan
-0.8246936756384636 -0.17253751292466876 native-country=Greece
0.8767567492400223 1.009877100465332 native-country=South
-0.431313830984111 -0.36931474546125737 native-country=China
0.2500983020742322 -3.026792942058025 native-country=Cuba
-0.1594185695248333 -0.06513020283624513 native-country=Iran
-0.6159092691404728 -0.7355781413237934 native-country=Honduras
0.9891320194682877 -0.9556312960073118 native-country=Philippines
-0.3884662623357531 -0.10382353796983083 native-country=Italy
-0.4833116724730438 -2.228134778061854 native-country=Poland
0.02790983497768432 -0.747538231466499 native-country=Jamaica
-0.17546682502680022 -0.786075557557705 native-country=Vietnam
0.2795816670928768 0.9934897228812976 native-country=Mexico
0.6663281095743692 -2.4306037270677208 native-country=Portugal
-0.7661198766593512 -1.0392172641706292 native-country=Ireland
0.9317380524761589 -0.5614498510776799 native-country=France
0.3682275968519289 -0.41735146945617535 native-country=Dominican-Republic
-0.12489341608558306 -1.8514593503298429 native-country=Laos
-0.19762427571125424 -2.2060703860089648 native-country=Ecuador
0.6993146987375795 0.4219225890208623 native-country=Taiwan
-0.6249758094122477 -1.22843377764972 native-country=Haiti
0.41871402771272076 -1.1104231238717026 native-country=Columbia
0.023155088069760774 0.03643631283500194 native-country=Hungary
-0.08484716500544535 0.7069982846065752 native-country=Guatemala
0.0856767422604451 -0.6754468339648865 native-country=Nicaragua
0.387245327135343 0.3997729122133378 native-country=Scotland
-0.8820948643745746 -0.3667348825939262 native-country=Thailand
-0.29189052203715515 0.6523528223818207 native-country=Yugoslavia
0.04721313009064191 -0.9192889293062013 native-country=El-Salvador
-0.5681654252076763 -0.6621127051949818 native-country=Trinadad&Tobago
0.023199904443176097 -1.194778822514238 native-country=Peru
-0.41637162621272983 -0.25681296618131116 native-country=Hong
0.6721528473008557 -0.21810312796513706 native-country=Holand-Netherlands
Hidden Weights:
-2.296979326593888 2.2900267010978155
6.995684099953782 -6.99164666005314
>50K <=50K
=== Error on training data ===
Correctly Classified Instances 461 89.5146 %
Incorrectly Classified Instances 54 10.4854 %
Mean absolute error 0.2177
Root mean squared error 0.2859
Relative absolute error 63.0554 %
Root relative squared error 68.8663 %
Total Number of Instances 515
=== Confusion Matrix ===
a b <-- classified as
73 41 | a = >50K
13 388 | b = <=50K
=== Error on test data ===
Correctly Classified Instances 419 81.3592 %
Incorrectly Classified Instances 96 18.6408 %
Mean absolute error 0.2702
Root mean squared error 0.3706
Relative absolute error 77.0456 %
Root relative squared error 87.8937 %
Total Number of Instances 515
=== Confusion Matrix ===
a b <-- classified as
56 63 | a = >50K
33 363 | b = <=50K
|
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