text: -- This SQL code was generated by sklearn2sql (development version).
  -- Copyright 2018
  
  -- Model : CaretRegressor_nnet_pca
  -- Dataset : RandomReg_10
  -- Database : pgsql
  
  
  -- This SQL code can contain one or more statements, to be executed in the order they appear in this file.
  
  
  
  -- Model deployment code
  
  WITH "ADS_sca_1_OUT" AS 
  (SELECT "ADS"."KEY" AS "KEY", (CAST("ADS"."Feature_0" AS FLOAT) - 0.1668094729813739) / 1.03547567419981 AS "Feature_0", (CAST("ADS"."Feature_1" AS FLOAT) - -0.1635127199444346) / 0.9978373487111776 AS "Feature_1", (CAST("ADS"."Feature_2" AS FLOAT) - 0.19149292241003152) / 0.9379956714934372 AS "Feature_2", (CAST("ADS"."Feature_3" AS FLOAT) - 0.05838484475305535) / 1.092422041481253 AS "Feature_3", (CAST("ADS"."Feature_4" AS FLOAT) - -0.09933205162122273) / 1.081168997121092 AS "Feature_4", (CAST("ADS"."Feature_5" AS FLOAT) - 0.21293121660488026) / 0.9417116446342017 AS "Feature_5", (CAST("ADS"."Feature_6" AS FLOAT) - 0.0478655686900296) / 1.1435269275597653 AS "Feature_6", (CAST("ADS"."Feature_7" AS FLOAT) - 0.05078698959084227) / 0.9786817421858578 AS "Feature_7", (CAST("ADS"."Feature_8" AS FLOAT) - -0.19131992259081876) / 1.1488000469275086 AS "Feature_8", (CAST("ADS"."Feature_9" AS FLOAT) - 0.1994040567747336) / 0.8878119561240071 AS "Feature_9" 
  FROM "RandomReg_10" AS "ADS"), 
  "ADS_pre_1_OUT" AS 
  (SELECT "ADS_sca_1_OUT"."KEY" AS "KEY", "ADS_sca_1_OUT"."Feature_0" * 0.1456841447657754 + "ADS_sca_1_OUT"."Feature_1" * 0.01052326111479696 + "ADS_sca_1_OUT"."Feature_2" * 0.06914860134209275 + "ADS_sca_1_OUT"."Feature_3" * 0.395081446850409 + "ADS_sca_1_OUT"."Feature_4" * 0.5653788508678024 + "ADS_sca_1_OUT"."Feature_5" * -0.4234978636491337 + "ADS_sca_1_OUT"."Feature_6" * -0.13347391731421338 + "ADS_sca_1_OUT"."Feature_7" * 0.5073597310574229 + "ADS_sca_1_OUT"."Feature_8" * 0.17681881915451916 + "ADS_sca_1_OUT"."Feature_9" * 0.11089070562205412 AS "PC1", "ADS_sca_1_OUT"."Feature_0" * -0.28606729371603284 + "ADS_sca_1_OUT"."Feature_1" * -0.1416224223949325 + "ADS_sca_1_OUT"."Feature_2" * -0.21284760934172509 + "ADS_sca_1_OUT"."Feature_3" * -0.2570681745801655 + "ADS_sca_1_OUT"."Feature_4" * 0.22505517518455515 + "ADS_sca_1_OUT"."Feature_5" * -0.01568473246748345 + "ADS_sca_1_OUT"."Feature_6" * -0.5725136264722785 + "ADS_sca_1_OUT"."Feature_7" * -0.08820208123478704 + "ADS_sca_1_OUT"."Feature_8" * -0.3605522366090105 + "ADS_sca_1_OUT"."Feature_9" * 0.5198800093216087 AS "PC2", "ADS_sca_1_OUT"."Feature_0" * 0.3393859060808712 + "ADS_sca_1_OUT"."Feature_1" * 0.4706204946180642 + "ADS_sca_1_OUT"."Feature_2" * 0.4682237189969609 + "ADS_sca_1_OUT"."Feature_3" * -0.24873660011955734 + "ADS_sca_1_OUT"."Feature_4" * 0.30955843893203433 + "ADS_sca_1_OUT"."Feature_5" * 0.27598076274469385 + "ADS_sca_1_OUT"."Feature_6" * -0.3878587432228167 + "ADS_sca_1_OUT"."Feature_7" * -0.1713140961495792 + "ADS_sca_1_OUT"."Feature_8" * 0.041332656018300086 + "ADS_sca_1_OUT"."Feature_9" * -0.16954966329100976 AS "PC3", "ADS_sca_1_OUT"."Feature_0" * 0.38499125608277135 + "ADS_sca_1_OUT"."Feature_1" * -0.4892407072526046 + "ADS_sca_1_OUT"."Feature_2" * 0.4525070336744841 + "ADS_sca_1_OUT"."Feature_3" * -0.11446163468336185 + "ADS_sca_1_OUT"."Feature_4" * -0.08228589793601762 + "ADS_sca_1_OUT"."Feature_5" * 0.05835205758419686 + "ADS_sca_1_OUT"."Feature_6" * 0.13193485154948764 + "ADS_sca_1_OUT"."Feature_7" * 0.2747942471701797 + "ADS_sca_1_OUT"."Feature_8" * -0.535971424967745 + "ADS_sca_1_OUT"."Feature_9" * 0.06481665241973472 AS "PC4", "ADS_sca_1_OUT"."Feature_0" * -0.4241318059513543 + "ADS_sca_1_OUT"."Feature_1" * -0.12904202328161374 + "ADS_sca_1_OUT"."Feature_2" * 0.4375442860931951 + "ADS_sca_1_OUT"."Feature_3" * 0.3534858161601103 + "ADS_sca_1_OUT"."Feature_4" * 0.14097295746133154 + "ADS_sca_1_OUT"."Feature_5" * 0.5320793223160138 + "ADS_sca_1_OUT"."Feature_6" * 0.15027430836617292 + "ADS_sca_1_OUT"."Feature_7" * -0.03078935335662195 + "ADS_sca_1_OUT"."Feature_8" * 0.20609808144469807 + "ADS_sca_1_OUT"."Feature_9" * 0.3436198360204909 AS "PC5", "ADS_sca_1_OUT"."Feature_0" * 0.16994011109828247 + "ADS_sca_1_OUT"."Feature_1" * 0.33484071907765084 + "ADS_sca_1_OUT"."Feature_2" * 0.10471628928699762 + "ADS_sca_1_OUT"."Feature_3" * 0.5541013299742117 + "ADS_sca_1_OUT"."Feature_4" * -0.14490660804802982 + "ADS_sca_1_OUT"."Feature_5" * -0.26123038722761205 + "ADS_sca_1_OUT"."Feature_6" * 0.06579599409431937 + "ADS_sca_1_OUT"."Feature_7" * -0.4582634526572295 + "ADS_sca_1_OUT"."Feature_8" * -0.4058380481420916 + "ADS_sca_1_OUT"."Feature_9" * 0.26968500124997136 AS "PC6", "ADS_sca_1_OUT"."Feature_0" * 0.4370347300341415 + "ADS_sca_1_OUT"."Feature_1" * 0.3004814913700811 + "ADS_sca_1_OUT"."Feature_2" * -0.29942592437311427 + "ADS_sca_1_OUT"."Feature_3" * -0.04148829060270187 + "ADS_sca_1_OUT"."Feature_4" * -0.2386399066951679 + "ADS_sca_1_OUT"."Feature_5" * 0.3468575401295237 + "ADS_sca_1_OUT"."Feature_6" * 0.08868221205015787 + "ADS_sca_1_OUT"."Feature_7" * 0.35236441046927025 + "ADS_sca_1_OUT"."Feature_8" * 0.13869954974668547 + "ADS_sca_1_OUT"."Feature_9" * 0.5466373750783862 AS "PC7" 
  FROM "ADS_sca_1_OUT"), 
  "IL" AS 
  (SELECT "ADS_pre_1_OUT"."KEY" AS "KEY", CAST("ADS_pre_1_OUT"."PC1" AS FLOAT) AS "PC1", CAST("ADS_pre_1_OUT"."PC2" AS FLOAT) AS "PC2", CAST("ADS_pre_1_OUT"."PC3" AS FLOAT) AS "PC3", CAST("ADS_pre_1_OUT"."PC4" AS FLOAT) AS "PC4", CAST("ADS_pre_1_OUT"."PC5" AS FLOAT) AS "PC5", CAST("ADS_pre_1_OUT"."PC6" AS FLOAT) AS "PC6", CAST("ADS_pre_1_OUT"."PC7" AS FLOAT) AS "PC7" 
  FROM "ADS_pre_1_OUT"), 
  "HL_BA_1" AS 
  (SELECT "IL"."KEY" AS "KEY", 83.97232 * "IL"."PC1" + -76.77144 * "IL"."PC2" + 112.8967 * "IL"."PC3" + -11.89547 * "IL"."PC4" + 106.3288 * "IL"."PC5" + -5.657423 * "IL"."PC6" + 59.44377 * "IL"."PC7" + 24.46676 AS "NEUR_1_1", 7.729126 * "IL"."PC1" + 5.969355 * "IL"."PC2" + 6.142141 * "IL"."PC3" + 14.96232 * "IL"."PC4" + 8.497759 * "IL"."PC5" + -7.25676 * "IL"."PC6" + 17.98674 * "IL"."PC7" + -64.53236 AS "NEUR_1_2", 103.4486 * "IL"."PC1" + -6.772398 * "IL"."PC2" + 32.30612 * "IL"."PC3" + -11.29283 * "IL"."PC4" + 61.9539 * "IL"."PC5" + -34.76305 * "IL"."PC6" + 24.94992 * "IL"."PC7" + -25.58717 AS "NEUR_1_3", -37.47276 * "IL"."PC1" + 93.07602 * "IL"."PC2" + -69.02543 * "IL"."PC3" + 41.73531 * "IL"."PC4" + -113.6599 * "IL"."PC5" + 6.390174 * "IL"."PC6" + -57.09446 * "IL"."PC7" + -37.58414 AS "NEUR_1_4", -35.64566 * "IL"."PC1" + 53.68354 * "IL"."PC2" + -44.44306 * "IL"."PC3" + 40.82629 * "IL"."PC4" + -77.61596 * "IL"."PC5" + 6.798126 * "IL"."PC6" + -52.01113 * "IL"."PC7" + -2.66334 AS "NEUR_1_5", 0.617433 * "IL"."PC1" + -3.011726 * "IL"."PC2" + -1.176188 * "IL"."PC3" + -2.271506 * "IL"."PC4" + -10.2573 * "IL"."PC5" + 3.877937 * "IL"."PC6" + 5.318785 * "IL"."PC7" + -65.87483 AS "NEUR_1_6", -118.8894 * "IL"."PC1" + -19.73958 * "IL"."PC2" + -60.8711 * "IL"."PC3" + 24.75927 * "IL"."PC4" + -46.00153 * "IL"."PC5" + 2.403381 * "IL"."PC6" + -15.89862 * "IL"."PC7" + -72.94179 AS "NEUR_1_7", -8.865129 * "IL"."PC1" + 9.630092 * "IL"."PC2" + 41.91367 * "IL"."PC3" + -52.35988 * "IL"."PC4" + 54.29812 * "IL"."PC5" + -14.46906 * "IL"."PC6" + 9.416569 * "IL"."PC7" + -1.156251 AS "NEUR_1_8", 54.60512 * "IL"."PC1" + 7.558424 * "IL"."PC2" + 19.42035 * "IL"."PC3" + -18.4314 * "IL"."PC4" + 50.46488 * "IL"."PC5" + -15.63529 * "IL"."PC6" + -16.13227 * "IL"."PC7" + 17.13527 AS "NEUR_1_9", -47.39415 * "IL"."PC1" + 0.4317514 * "IL"."PC2" + 46.25705 * "IL"."PC3" + 6.707527 * "IL"."PC4" + 5.637655 * "IL"."PC5" + 23.69139 * "IL"."PC6" + 43.27619 * "IL"."PC7" + -74.47519 AS "NEUR_1_10", -79.86396 * "IL"."PC1" + 96.12973 * "IL"."PC2" + -82.27485 * "IL"."PC3" + 33.15751 * "IL"."PC4" + -99.99094 * "IL"."PC5" + -17.0124 * "IL"."PC6" + -75.52756 * "IL"."PC7" + -18.45018 AS "NEUR_1_11", 71.95266 * "IL"."PC1" + -53.79583 * "IL"."PC2" + 15.07734 * "IL"."PC3" + 34.7564 * "IL"."PC4" + 29.46265 * "IL"."PC5" + -7.482735 * "IL"."PC6" + 66.06244 * "IL"."PC7" + -25.4109 AS "NEUR_1_12" 
  FROM "IL"), 
  "HL_1_logistic" AS 
  (SELECT "HL_BA_1"."KEY" AS "KEY", 1.0 / (1.0 + exp(least(100.0, greatest(-100.0, -"HL_BA_1"."NEUR_1_1")))) AS "NEUR_1_1", 1.0 / (1.0 + exp(least(100.0, greatest(-100.0, -"HL_BA_1"."NEUR_1_2")))) AS "NEUR_1_2", 1.0 / (1.0 + exp(least(100.0, greatest(-100.0, -"HL_BA_1"."NEUR_1_3")))) AS "NEUR_1_3", 1.0 / (1.0 + exp(least(100.0, greatest(-100.0, -"HL_BA_1"."NEUR_1_4")))) AS "NEUR_1_4", 1.0 / (1.0 + exp(least(100.0, greatest(-100.0, -"HL_BA_1"."NEUR_1_5")))) AS "NEUR_1_5", 1.0 / (1.0 + exp(least(100.0, greatest(-100.0, -"HL_BA_1"."NEUR_1_6")))) AS "NEUR_1_6", 1.0 / (1.0 + exp(least(100.0, greatest(-100.0, -"HL_BA_1"."NEUR_1_7")))) AS "NEUR_1_7", 1.0 / (1.0 + exp(least(100.0, greatest(-100.0, -"HL_BA_1"."NEUR_1_8")))) AS "NEUR_1_8", 1.0 / (1.0 + exp(least(100.0, greatest(-100.0, -"HL_BA_1"."NEUR_1_9")))) AS "NEUR_1_9", 1.0 / (1.0 + exp(least(100.0, greatest(-100.0, -"HL_BA_1"."NEUR_1_10")))) AS "NEUR_1_10", 1.0 / (1.0 + exp(least(100.0, greatest(-100.0, -"HL_BA_1"."NEUR_1_11")))) AS "NEUR_1_11", 1.0 / (1.0 + exp(least(100.0, greatest(-100.0, -"HL_BA_1"."NEUR_1_12")))) AS "NEUR_1_12" 
  FROM "HL_BA_1"), 
  "HL_1_logistic_1" AS 
  (SELECT "HL_1_logistic"."KEY" AS "KEY", "HL_1_logistic"."NEUR_1_1" AS "NEUR_1_1", "HL_1_logistic"."NEUR_1_2" AS "NEUR_1_2", "HL_1_logistic"."NEUR_1_3" AS "NEUR_1_3", "HL_1_logistic"."NEUR_1_4" AS "NEUR_1_4", "HL_1_logistic"."NEUR_1_5" AS "NEUR_1_5", "HL_1_logistic"."NEUR_1_6" AS "NEUR_1_6", "HL_1_logistic"."NEUR_1_7" AS "NEUR_1_7", "HL_1_logistic"."NEUR_1_8" AS "NEUR_1_8", "HL_1_logistic"."NEUR_1_9" AS "NEUR_1_9", "HL_1_logistic"."NEUR_1_10" AS "NEUR_1_10", "HL_1_logistic"."NEUR_1_11" AS "NEUR_1_11", "HL_1_logistic"."NEUR_1_12" AS "NEUR_1_12" 
  FROM "HL_1_logistic"), 
  "OL_BA" AS 
  (SELECT "HL_1_logistic_1"."KEY" AS "KEY", 21.4479 * "HL_1_logistic_1"."NEUR_1_1" + 260.9546 * "HL_1_logistic_1"."NEUR_1_2" + 110.8445 * "HL_1_logistic_1"."NEUR_1_3" + -138.5386 * "HL_1_logistic_1"."NEUR_1_4" + -48.62121 * "HL_1_logistic_1"."NEUR_1_5" + 134.6655 * "HL_1_logistic_1"."NEUR_1_6" + -47.29779 * "HL_1_logistic_1"."NEUR_1_7" + 122.2525 * "HL_1_logistic_1"."NEUR_1_8" + -27.00906 * "HL_1_logistic_1"."NEUR_1_9" + 95.97373 * "HL_1_logistic_1"."NEUR_1_10" + 48.36984 * "HL_1_logistic_1"."NEUR_1_11" + 157.6943 * "HL_1_logistic_1"."NEUR_1_12" + -80.39637 AS "NEUR_2_1" 
  FROM "HL_1_logistic_1"), 
  "OL_identity" AS 
  (SELECT "OL_BA"."KEY" AS "KEY", "OL_BA"."NEUR_2_1" AS "NEUR_2_1" 
  FROM "OL_BA"), 
  "OL_identity_1" AS 
  (SELECT "OL_identity"."KEY" AS "KEY", "OL_identity"."NEUR_2_1" AS "NEUR_2_1" 
  FROM "OL_identity")
   SELECT "OL_identity_1"."KEY" AS "KEY", "OL_identity_1"."NEUR_2_1" AS "Estimator" 
  FROM "OL_identity_1"