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[kaggle]Analytics Vidhya Loan Prediction | {'X_num': {'ApplicantIncome': {0: -1.5474634170532227, 1: -1.1698240041732788, 2: -0.9614736437797546, 3: -1.3783310651779175, 4: -0.4060468375682831, 5: -1.4718408584594727, 6: 0.8235251307487488, 7: -0.9806960821151733, 8: -1.3203742504119873, 9: 0.7123724222183228, 10: 0.051976729184389114, 11: 0.199598029255867, 12: -0.673802375793457, 13: -1.4276002645492554, 14: 0.7708829045295715, 15: 0.03146321699023247, 16: -0.8261409997940063, 17: 0.8645530343055725, 18: -0.9614736437797546, 19: -0.39630329608917236, 20: -1.6050407886505127, 21: 0.7200467586517334, 22: 1.3854714632034302, 23: 1.2680089473724365, 24: -0.9759913086891174, 25: 0.3515683114528656, 26: 1.3855332136154175, 27: 1.4278597831726074, 28: -0.33253562450408936, 29: 0.6201209425926208, 30: -1.4080486297607422, 31: -1.262650728225708, 32: 0.29620471596717834, 33: -0.8917647004127502, 34: -0.6260018944740295, 35: 0.3660774230957031, 36: -0.7852975130081177, 37: 0.0844649001955986, 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{'policy': 'default'}} | binclass |
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[kaggle]Customer Classification | {'X_num': {'tenure': {0: -0.5691838264465332, 1: -1.833905816078186, 2: -1.026270866394043, 3: 4.591024875640869, 4: 0.18911808729171753, 5: -0.7949101328849792, 6: 0.5977593064308167, 7: 0.22111865878105164, 8: -1.1873492002487183, 9: 0.7063034772872925, 10: 1.2815507650375366, 11: -1.026270866394043, 12: 0.7063034772872925, 13: -1.281545877456665, 14: -0.3853185474872589, 15: 0.5243968963623047, 16: 0.15731008350849152, 17: 0.9674264788627625, 18: -0.22754690051078796, 19: -0.8997495770454407, 20: 1.6448609828948975, 21: -0.6151400804519653, 22: 0.6356568932533264, 23: 0.902739942073822, 24: -0.041790977120399475, 25: 0.8416264057159424, 26: -2.1280243396759033, 27: -1.281545877456665, 28: 0.2793193757534027, 29: 4.591024875640869, 30: -2.1280243396759033, 31: -1.1873492002487183, 32: -1.026270866394043, 33: -1.1026532649993896, 34: -0.5691838264465332, 35: 1.1503511667251587, 36: 0.5607017278671265, 37: -1.833905816078186, 38: -0.7949101328849792, 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[kaggle]Startup Success Prediction | {'X_num': {'latitude': {0: -2.781088352203369, 1: 0.4033139646053314, 2: -0.5086419582366943, 3: 0.0027986897621303797, 4: 0.609723687171936, 5: 0.1403888761997223, 6: -0.7210291028022766, 7: -0.5772526264190674, 8: -0.7635112404823303, 9: 1.745227575302124, 10: -0.018150771036744118, 11: 0.7654547095298767, 12: 0.5227352380752563, 13: -1.605508804321289, 14: -0.5772526264190674, 15: 0.5964686274528503, 16: 1.2842705249786377, 17: -1.2441298961639404, 18: -1.212288498878479, 19: -0.6208729147911072, 20: -0.6388225555419922, 21: -0.009519441053271294, 22: 0.42221561074256897, 23: -1.80585515499115, 24: -0.7082186937332153, 25: -0.9033540487289429, 26: 0.609723687171936, 27: -1.594223141670227, 28: -0.39701125025749207, 29: -0.25785988569259644, 30: 1.7525217533111572, 31: 0.40022706985473633, 32: -0.3489488363265991, 33: 0.7709840536117554, 34: -0.9035955667495728, 35: -0.9810763597488403, 36: 1.3500481843948364, 37: 1.2636008262634277, 38: 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[openml]Swiss-banknote-conterfeit-detection | {'X_num': {'Length': {0: 0.42883262038230896, 1: 0.9686594009399414, 2: 0.42883262038230896, 3: -1.1996933221817017, 4: 0.9686594009399414, 5: -0.4288090169429779, 6: -0.1388797163963318, 7: -0.757807195186615, 8: 1.3490817546844482, 9: 1.2220700979232788, 10: 0.7597841024398804, 11: 0.42883262038230896, 12: 0.7597841024398804, 13: 0.7597841024398804, 14: -0.1388797163963318, 15: -0.4288090169429779, 16: -1.1996933221817017, 17: 1.2220700979232788, 18: 1.4216639995574951, 19: -0.1388797163963318, 20: -0.1388797163963318, 21: 0.42883262038230896, 22: 0.9686594009399414, 23: -0.4288090169429779, 24: -1.4077873229980469, 25: -1.6696741580963135, 26: -1.4077873229980469, 27: 0.14373451471328735, 28: 1.2829842567443848, 29: -0.4288090169429779, 30: 0.9686594009399414, 31: -0.1388797163963318, 32: 0.42883262038230896, 33: -1.3067526817321777, 34: 0.7597841024398804, 35: -0.757807195186615, 36: -1.1996933221817017, 37: -0.757807195186615, 38: 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[UCI]Absenteeism at work | {'X_num': {'Reasonforabsence': {0: 0.16680794954299927, 1: -0.31864258646965027, 2: 0.7916561365127563, 3: -0.6363970637321472, 4: 1.464390516281128, 5: -1.1797587871551514, 6: 1.464390516281128, 7: -0.17998047173023224, 8: 1.464390516281128, 9: 0.16680794954299927, 10: 1.464390516281128, 11: 1.464390516281128, 12: -1.220638632774353, 13: 0.16680794954299927, 14: 0.16680794954299927, 15: -0.6363970637321472, 16: 0.5659788846969604, 17: -1.0675581693649292, 18: -0.31864258646965027, 19: -0.5244055986404419, 20: 1.464390516281128, 21: -0.6363970637321472, 22: 0.7916561365127563, 23: 1.464390516281128, 24: 0.16680794954299927, 25: 1.464390516281128, 26: 0.16680794954299927, 27: 1.464390516281128, 28: 1.464390516281128, 29: -4.213054180145264, 30: 0.5659788846969604, 31: -0.6363970637321472, 32: -1.0675581693649292, 33: 0.16680794954299927, 34: -0.9674064517021179, 35: 0.16680794954299927, 36: 1.464390516281128, 37: 0.7916561365127563, 38: -0.31864258646965027, 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regression |
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regression |
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Subsets and Splits