(Solved): Creating A Regression Model In R That Accurately Predicts Responding Variable 'Score'

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Posted 2022-04-25T01:37:38.000000Z

Modified 2022-04-25T01:37:38.000000Z

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This data challenge involves regression task. The target variable is 'score' that captures medical condition of a patient. Independent variables capture patient related data that can influence the target variable 'score'. First variable in the train.csv data file identifies each patient record uniquely. The challenge is to correctly predict value for 'score' based on independent variables. I am not a data scientist and I need help creating this model

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Id score V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 V14 V15 V16 V17 V18 V19 V20 V21 V22 V23 V24 V25 V26 V27 V28 V29 403 34.13 0.00243 1.757e-05 0.00108 0.00124 0.00323 0.01147 0.105 0.00625 0.00658 0.00834 0.01874 0.00575 28.897 0.46124 0.58305 0.12722 0.466721605152117 -0.824511225118934 -1.21787456728801 -0.432388821503959 -1.45531978890704 -0.280674551376605 0.681112849927389 0.375320150740958 0.764563076020874 -0.23785913776027 -0.28219840759496 1477 19 0.0028 2.118e-05 0.00087 0.00128 0.0026 0.01575 0.137 0.00812 0.00868 0.01072 0.02435 0.009616 26.027 0.55084 0.57033 0.12869 0.805984693271499 0.0804664524854719 -0.812559263060398 1.51273059800125 0.0703305640837706 2.36875385222961 -0.256309116835819 1.31599675980002 0.0936305859555036 -0.389538267384845 1.39609478369198 5342 43.104 0.00412 2.751e-05 0.00162 0.00213 0.00487 0.02644 0.242 0.0115 0.01423 0.02545 0.0345 0.019516 23.01 0.59287 0.60478 0.26151 2.03490210521593 -0.0605551746821582 -0.0277656994485174 -0.123652172438778 0.820478048918491 1.05443890924887 1.92214582249234 -1.26243543999906 2.01799651114069 0.687229224988068 -0.935456162734902 3812 38.814 0.00781 4.284e-05 0.00451 0.00399 0.01353 0.02975 0.261 0.0165 0.0161 0.02198 0.04951 0.019363 21.479 0.53716 0.75339 0.19362 -0.921909192878524 -0.153331911665301 -1.2982894126478 1.41048573568736 1.95001163341316 0.613255022252045 0.49241901562976 0.124454388570434 0.891332242013939 0.401178885771417 0.383194799811775 138 41.034 0.00488 2.568e-05 0.00265 0.00251 0.00794 0.04983 0.448 0.02688 0.02876 0.04052 0.08064 0.013138 23.136 0.46322 0.57274 0.19423 1.65076611173495 -0.985638670864032 -0.469064447525771 -2.57991950123096 0.17388358930429 -0.330941347235976 0.0895970669956078 0.617369246987926 -0.183966595371091 0.408726182950445 1.60787127431046 5004 45.326 0.00231 1.082e-05 0.00132 0.00125 0.00396 0.0318 0.283 0.01823 0.01679 0.02096 0.05468 0.01028 22.684 0.50143 0.58618 0.12266 -1.99407472032693 -0.295072686971263 0.936752707845099 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0.00395 2.174e-05 0.00174 0.00193 0.00523 0.02711 0.241 0.01353 0.0155 0.0238 0.04059 0.011726 25.707 0.43168 0.59563 0.17268 -1.29064844141999 -0.00080019601180786 0.958933067475722 -1.39773365955324 0.0803262132655165 1.03214226643535 0.97432571721995 0.682633751884082 0.19950866347427 0.219559831707543 1.8823040978606 4161 32.222 0.0038 3.506e-05 0.00153 0.00162 0.00458 0.00918 0.087 0.00332 0.00409 0.00782 0.00997 0.007235 25.84 0.58651 0.66463 0.1381 -1.10030468298414 -2.36281009137648 -0.269736102403041 1.89454053439414 0.257096677694836 -0.0180590363942522 -0.817224342740028 0.162147117601613 -0.107850220752023 -0.0233391506106984 -1.1659236908666 4941 32 0.00409 4.458e-05 0.00169 0.00231 0.00506 0.06424 0.544 0.02626 0.04214 0.06168 0.07879 0.053145 15.419 0.61054 0.58905 0.25085 0.30793811765389 -0.430520482262589 0.121325931731113 -0.330571188098209 2.09173990996298 0.418983716576123 0.420072354477472 1.31134257441423 0.726145106030351 0.158032142052282 -0.376053400346285 2014 23.132 0.00459 2.748e-05 0.00254 0.00218 0.00763 0.02227 0.2 0.01256 0.01166 0.01582 0.03768 0.016219 25.155 0.5001 0.61332 0.12364 -0.294343532883517 -0.543711875842901 0.790758904266242 1.76833968466327 -0.365552094864948 -1.99021928479505 1.46666825066588 0.785996577617361 0.147497355585465 0.304524495524671 0.498809705964797 3880 30.082 0.00379 2.153e-05 0.00142 0.00177 0.00426 0.03151 0.308 0.01582 0.0184 0.0249 0.04746 0.014253 24.929 0.40658 0.62982 0.16996 -1.84036068882199 0.588043977365955 -0.529005187569193 -2.10779796514986 0.178179447719037 0.597129773583108 0.618622324689827 -1.96780764695328 -0.0171665205198696 -0.939200703373606 0.346540051650209 3871 25.767 0.01208 6.83e-05 0.00706 0.00656 0.02117 0.0352 0.281 0.01611 0.0191 0.02777 0.04832 0.044095 17.957 0.67483 0.70835 0.44841 -0.318816157537475 -1.50647842862445 -0.389711812452017 -0.406195109250431 -1.62661652281901 0.307940617478008 -0.811396817978053 -0.762831330189686 -1.74108552614657 -0.536512810794176 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-0.430344910885548 -1.00912701269168 700 40.155 0.00271 2.092e-05 0.00125 0.00162 0.00374 0.02913 0.254 0.01581 0.01816 0.02337 0.04743 0.005903 24.292 0.52778 0.59432 0.14466 -1.81610004452046 0.406129452729642 0.11475474713698 0.616668389359306 0.224477705623686 -0.163300533941841 0.522177166597783 -0.388088277999979 1.09129698818229 -0.841083575672684 0.90041633546025 4100 30.922 0.0047 5.049e-05 0.00121 0.00179 0.00364 0.01189 0.115 0.00439 0.00569 0.01071 0.01318 0.019011 20.08 0.69224 0.71839 0.097282 -1.95899581509617 -0.495366039317759 -1.16322080764145 -0.981338640852614 -0.749109416537695 0.0937815023356308 -0.571813988295907 -0.221883097308548 -0.72087242906862 1.10013973657227 1.39392724602664 1375 21.922 0.00585 5.328e-05 0.0025 0.0022 0.00749 0.02524 0.23 0.0128 0.0135 0.01665 0.03839 0.032603 23.826 0.53713 0.6738 0.22852 -0.224003359158025 0.990616984784456 -0.385557423516213 -0.949009992827133 -0.99292355826242 -0.0622636086042134 -0.919916403315146 0.969849883702149 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