text: -- This SQL code was generated by sklearn2sql (development version).
  -- Copyright 2018
  
  -- Model : KerasRegressor_LSTM
  -- Dataset : RandomReg_100
  -- Database : mysql
  
  
  -- This SQL code can contain one or more statements, to be executed in the order they appear in this file.
  
  
  
  -- Model deployment code
  
  WITH RECURSIVE keras_input AS 
  (SELECT `ADS`.`KEY` AS `KEY`, `ADS`.`Feature_0` AS `Feature_0`, `ADS`.`Feature_1` AS `Feature_1`, `ADS`.`Feature_2` AS `Feature_2`, `ADS`.`Feature_3` AS `Feature_3`, `ADS`.`Feature_4` AS `Feature_4`, `ADS`.`Feature_5` AS `Feature_5`, `ADS`.`Feature_6` AS `Feature_6`, `ADS`.`Feature_7` AS `Feature_7`, `ADS`.`Feature_8` AS `Feature_8`, `ADS`.`Feature_9` AS `Feature_9`, `ADS`.`Feature_10` AS `Feature_10`, `ADS`.`Feature_11` AS `Feature_11`, `ADS`.`Feature_12` AS `Feature_12`, `ADS`.`Feature_13` AS `Feature_13`, `ADS`.`Feature_14` AS `Feature_14`, `ADS`.`Feature_15` AS `Feature_15`, `ADS`.`Feature_16` AS `Feature_16`, `ADS`.`Feature_17` AS `Feature_17`, `ADS`.`Feature_18` AS `Feature_18`, `ADS`.`Feature_19` AS `Feature_19`, `ADS`.`Feature_20` AS `Feature_20`, `ADS`.`Feature_21` AS `Feature_21`, `ADS`.`Feature_22` AS `Feature_22`, `ADS`.`Feature_23` AS `Feature_23`, `ADS`.`Feature_24` AS `Feature_24`, `ADS`.`Feature_25` AS `Feature_25`, `ADS`.`Feature_26` AS `Feature_26`, `ADS`.`Feature_27` AS `Feature_27`, `ADS`.`Feature_28` AS `Feature_28`, `ADS`.`Feature_29` AS `Feature_29`, `ADS`.`Feature_30` AS `Feature_30`, `ADS`.`Feature_31` AS `Feature_31`, `ADS`.`Feature_32` AS `Feature_32`, `ADS`.`Feature_33` AS `Feature_33`, `ADS`.`Feature_34` AS `Feature_34`, `ADS`.`Feature_35` AS `Feature_35`, `ADS`.`Feature_36` AS `Feature_36`, `ADS`.`Feature_37` AS `Feature_37`, `ADS`.`Feature_38` AS `Feature_38`, `ADS`.`Feature_39` AS `Feature_39`, `ADS`.`Feature_40` AS `Feature_40`, `ADS`.`Feature_41` AS `Feature_41`, `ADS`.`Feature_42` AS `Feature_42`, `ADS`.`Feature_43` AS `Feature_43`, `ADS`.`Feature_44` AS `Feature_44`, `ADS`.`Feature_45` AS `Feature_45`, `ADS`.`Feature_46` AS `Feature_46`, `ADS`.`Feature_47` AS `Feature_47`, `ADS`.`Feature_48` AS `Feature_48`, `ADS`.`Feature_49` AS `Feature_49`, `ADS`.`Feature_50` AS `Feature_50`, `ADS`.`Feature_51` AS `Feature_51`, `ADS`.`Feature_52` AS `Feature_52`, `ADS`.`Feature_53` AS `Feature_53`, `ADS`.`Feature_54` AS `Feature_54`, `ADS`.`Feature_55` AS `Feature_55`, `ADS`.`Feature_56` AS `Feature_56`, `ADS`.`Feature_57` AS `Feature_57`, `ADS`.`Feature_58` AS `Feature_58`, `ADS`.`Feature_59` AS `Feature_59`, `ADS`.`Feature_60` AS `Feature_60`, `ADS`.`Feature_61` AS `Feature_61`, `ADS`.`Feature_62` AS `Feature_62`, `ADS`.`Feature_63` AS `Feature_63`, `ADS`.`Feature_64` AS `Feature_64`, `ADS`.`Feature_65` AS `Feature_65`, `ADS`.`Feature_66` AS `Feature_66`, `ADS`.`Feature_67` AS `Feature_67`, `ADS`.`Feature_68` AS `Feature_68`, `ADS`.`Feature_69` AS `Feature_69`, `ADS`.`Feature_70` AS `Feature_70`, `ADS`.`Feature_71` AS `Feature_71`, `ADS`.`Feature_72` AS `Feature_72`, `ADS`.`Feature_73` AS `Feature_73`, `ADS`.`Feature_74` AS `Feature_74`, `ADS`.`Feature_75` AS `Feature_75`, `ADS`.`Feature_76` AS `Feature_76`, `ADS`.`Feature_77` AS `Feature_77`, `ADS`.`Feature_78` AS `Feature_78`, `ADS`.`Feature_79` AS `Feature_79`, `ADS`.`Feature_80` AS `Feature_80`, `ADS`.`Feature_81` AS `Feature_81`, `ADS`.`Feature_82` AS `Feature_82`, `ADS`.`Feature_83` AS `Feature_83`, `ADS`.`Feature_84` AS `Feature_84`, `ADS`.`Feature_85` AS `Feature_85`, `ADS`.`Feature_86` AS `Feature_86`, `ADS`.`Feature_87` AS `Feature_87`, `ADS`.`Feature_88` AS `Feature_88`, `ADS`.`Feature_89` AS `Feature_89`, `ADS`.`Feature_90` AS `Feature_90`, `ADS`.`Feature_91` AS `Feature_91`, `ADS`.`Feature_92` AS `Feature_92`, `ADS`.`Feature_93` AS `Feature_93`, `ADS`.`Feature_94` AS `Feature_94`, `ADS`.`Feature_95` AS `Feature_95`, `ADS`.`Feature_96` AS `Feature_96`, `ADS`.`Feature_97` AS `Feature_97`, `ADS`.`Feature_98` AS `Feature_98`, `ADS`.`Feature_99` AS `Feature_99` 
  FROM `RandomReg_100` AS `ADS`), 
  keras_input_1 AS 
  (SELECT keras_input.`KEY` AS `KEY`, keras_input.`Feature_0` AS `Feature_0`, keras_input.`Feature_1` AS `Feature_1`, keras_input.`Feature_2` AS `Feature_2`, keras_input.`Feature_3` AS `Feature_3`, keras_input.`Feature_4` AS `Feature_4`, keras_input.`Feature_5` AS `Feature_5`, keras_input.`Feature_6` AS `Feature_6`, keras_input.`Feature_7` AS `Feature_7`, keras_input.`Feature_8` AS `Feature_8`, keras_input.`Feature_9` AS `Feature_9`, keras_input.`Feature_10` AS `Feature_10`, keras_input.`Feature_11` AS `Feature_11`, keras_input.`Feature_12` AS `Feature_12`, keras_input.`Feature_13` AS `Feature_13`, keras_input.`Feature_14` AS `Feature_14`, keras_input.`Feature_15` AS `Feature_15`, keras_input.`Feature_16` AS `Feature_16`, keras_input.`Feature_17` AS `Feature_17`, keras_input.`Feature_18` AS `Feature_18`, keras_input.`Feature_19` AS `Feature_19`, keras_input.`Feature_20` AS `Feature_20`, keras_input.`Feature_21` AS `Feature_21`, keras_input.`Feature_22` AS `Feature_22`, keras_input.`Feature_23` AS `Feature_23`, keras_input.`Feature_24` AS `Feature_24`, keras_input.`Feature_25` AS `Feature_25`, keras_input.`Feature_26` AS `Feature_26`, keras_input.`Feature_27` AS `Feature_27`, keras_input.`Feature_28` AS `Feature_28`, keras_input.`Feature_29` AS `Feature_29`, keras_input.`Feature_30` AS `Feature_30`, keras_input.`Feature_31` AS `Feature_31`, keras_input.`Feature_32` AS `Feature_32`, keras_input.`Feature_33` AS `Feature_33`, keras_input.`Feature_34` AS `Feature_34`, keras_input.`Feature_35` AS `Feature_35`, keras_input.`Feature_36` AS `Feature_36`, keras_input.`Feature_37` AS `Feature_37`, keras_input.`Feature_38` AS `Feature_38`, keras_input.`Feature_39` AS `Feature_39`, keras_input.`Feature_40` AS `Feature_40`, keras_input.`Feature_41` AS `Feature_41`, keras_input.`Feature_42` AS `Feature_42`, keras_input.`Feature_43` AS `Feature_43`, keras_input.`Feature_44` AS `Feature_44`, keras_input.`Feature_45` AS `Feature_45`, keras_input.`Feature_46` AS `Feature_46`, keras_input.`Feature_47` AS `Feature_47`, keras_input.`Feature_48` AS `Feature_48`, keras_input.`Feature_49` AS `Feature_49`, keras_input.`Feature_50` AS `Feature_50`, keras_input.`Feature_51` AS `Feature_51`, keras_input.`Feature_52` AS `Feature_52`, keras_input.`Feature_53` AS `Feature_53`, keras_input.`Feature_54` AS `Feature_54`, keras_input.`Feature_55` AS `Feature_55`, keras_input.`Feature_56` AS `Feature_56`, keras_input.`Feature_57` AS `Feature_57`, keras_input.`Feature_58` AS `Feature_58`, keras_input.`Feature_59` AS `Feature_59`, keras_input.`Feature_60` AS `Feature_60`, keras_input.`Feature_61` AS `Feature_61`, keras_input.`Feature_62` AS `Feature_62`, keras_input.`Feature_63` AS `Feature_63`, keras_input.`Feature_64` AS `Feature_64`, keras_input.`Feature_65` AS `Feature_65`, keras_input.`Feature_66` AS `Feature_66`, keras_input.`Feature_67` AS `Feature_67`, keras_input.`Feature_68` AS `Feature_68`, keras_input.`Feature_69` AS `Feature_69`, keras_input.`Feature_70` AS `Feature_70`, keras_input.`Feature_71` AS `Feature_71`, keras_input.`Feature_72` AS `Feature_72`, keras_input.`Feature_73` AS `Feature_73`, keras_input.`Feature_74` AS `Feature_74`, keras_input.`Feature_75` AS `Feature_75`, keras_input.`Feature_76` AS `Feature_76`, keras_input.`Feature_77` AS `Feature_77`, keras_input.`Feature_78` AS `Feature_78`, keras_input.`Feature_79` AS `Feature_79`, keras_input.`Feature_80` AS `Feature_80`, keras_input.`Feature_81` AS `Feature_81`, keras_input.`Feature_82` AS `Feature_82`, keras_input.`Feature_83` AS `Feature_83`, keras_input.`Feature_84` AS `Feature_84`, keras_input.`Feature_85` AS `Feature_85`, keras_input.`Feature_86` AS `Feature_86`, keras_input.`Feature_87` AS `Feature_87`, keras_input.`Feature_88` AS `Feature_88`, keras_input.`Feature_89` AS `Feature_89`, keras_input.`Feature_90` AS `Feature_90`, keras_input.`Feature_91` AS `Feature_91`, keras_input.`Feature_92` AS `Feature_92`, keras_input.`Feature_93` AS `Feature_93`, keras_input.`Feature_94` AS `Feature_94`, keras_input.`Feature_95` AS `Feature_95`, keras_input.`Feature_96` AS `Feature_96`, keras_input.`Feature_97` AS `Feature_97`, keras_input.`Feature_98` AS `Feature_98`, keras_input.`Feature_99` AS `Feature_99` 
  FROM keras_input), 
  keras_input_1_rn AS 
  (SELECT row_number() OVER (ORDER BY keras_input_1.`KEY` ASC) AS rn, keras_input_1.`KEY` AS `KEY`, keras_input_1.`Feature_0` AS `Feature_0`, keras_input_1.`Feature_1` AS `Feature_1`, keras_input_1.`Feature_2` AS `Feature_2`, keras_input_1.`Feature_3` AS `Feature_3`, keras_input_1.`Feature_4` AS `Feature_4`, keras_input_1.`Feature_5` AS `Feature_5`, keras_input_1.`Feature_6` AS `Feature_6`, keras_input_1.`Feature_7` AS `Feature_7`, keras_input_1.`Feature_8` AS `Feature_8`, keras_input_1.`Feature_9` AS `Feature_9`, keras_input_1.`Feature_10` AS `Feature_10`, keras_input_1.`Feature_11` AS `Feature_11`, keras_input_1.`Feature_12` AS `Feature_12`, keras_input_1.`Feature_13` AS `Feature_13`, keras_input_1.`Feature_14` AS `Feature_14`, keras_input_1.`Feature_15` AS `Feature_15`, keras_input_1.`Feature_16` AS `Feature_16`, keras_input_1.`Feature_17` AS `Feature_17`, keras_input_1.`Feature_18` AS `Feature_18`, keras_input_1.`Feature_19` AS `Feature_19`, keras_input_1.`Feature_20` AS `Feature_20`, keras_input_1.`Feature_21` AS `Feature_21`, keras_input_1.`Feature_22` AS `Feature_22`, keras_input_1.`Feature_23` AS `Feature_23`, keras_input_1.`Feature_24` AS `Feature_24`, keras_input_1.`Feature_25` AS `Feature_25`, keras_input_1.`Feature_26` AS `Feature_26`, keras_input_1.`Feature_27` AS `Feature_27`, keras_input_1.`Feature_28` AS `Feature_28`, keras_input_1.`Feature_29` AS `Feature_29`, keras_input_1.`Feature_30` AS `Feature_30`, keras_input_1.`Feature_31` AS `Feature_31`, keras_input_1.`Feature_32` AS `Feature_32`, keras_input_1.`Feature_33` AS `Feature_33`, keras_input_1.`Feature_34` AS `Feature_34`, keras_input_1.`Feature_35` AS `Feature_35`, keras_input_1.`Feature_36` AS `Feature_36`, keras_input_1.`Feature_37` AS `Feature_37`, keras_input_1.`Feature_38` AS `Feature_38`, keras_input_1.`Feature_39` AS `Feature_39`, keras_input_1.`Feature_40` AS `Feature_40`, keras_input_1.`Feature_41` AS `Feature_41`, keras_input_1.`Feature_42` AS `Feature_42`, keras_input_1.`Feature_43` AS `Feature_43`, keras_input_1.`Feature_44` AS `Feature_44`, keras_input_1.`Feature_45` AS `Feature_45`, keras_input_1.`Feature_46` AS `Feature_46`, keras_input_1.`Feature_47` AS `Feature_47`, keras_input_1.`Feature_48` AS `Feature_48`, keras_input_1.`Feature_49` AS `Feature_49`, keras_input_1.`Feature_50` AS `Feature_50`, keras_input_1.`Feature_51` AS `Feature_51`, keras_input_1.`Feature_52` AS `Feature_52`, keras_input_1.`Feature_53` AS `Feature_53`, keras_input_1.`Feature_54` AS `Feature_54`, keras_input_1.`Feature_55` AS `Feature_55`, keras_input_1.`Feature_56` AS `Feature_56`, keras_input_1.`Feature_57` AS `Feature_57`, keras_input_1.`Feature_58` AS `Feature_58`, keras_input_1.`Feature_59` AS `Feature_59`, keras_input_1.`Feature_60` AS `Feature_60`, keras_input_1.`Feature_61` AS `Feature_61`, keras_input_1.`Feature_62` AS `Feature_62`, keras_input_1.`Feature_63` AS `Feature_63`, keras_input_1.`Feature_64` AS `Feature_64`, keras_input_1.`Feature_65` AS `Feature_65`, keras_input_1.`Feature_66` AS `Feature_66`, keras_input_1.`Feature_67` AS `Feature_67`, keras_input_1.`Feature_68` AS `Feature_68`, keras_input_1.`Feature_69` AS `Feature_69`, keras_input_1.`Feature_70` AS `Feature_70`, keras_input_1.`Feature_71` AS `Feature_71`, keras_input_1.`Feature_72` AS `Feature_72`, keras_input_1.`Feature_73` AS `Feature_73`, keras_input_1.`Feature_74` AS `Feature_74`, keras_input_1.`Feature_75` AS `Feature_75`, keras_input_1.`Feature_76` AS `Feature_76`, keras_input_1.`Feature_77` AS `Feature_77`, keras_input_1.`Feature_78` AS `Feature_78`, keras_input_1.`Feature_79` AS `Feature_79`, keras_input_1.`Feature_80` AS `Feature_80`, keras_input_1.`Feature_81` AS `Feature_81`, keras_input_1.`Feature_82` AS `Feature_82`, keras_input_1.`Feature_83` AS `Feature_83`, keras_input_1.`Feature_84` AS `Feature_84`, keras_input_1.`Feature_85` AS `Feature_85`, keras_input_1.`Feature_86` AS `Feature_86`, keras_input_1.`Feature_87` AS `Feature_87`, keras_input_1.`Feature_88` AS `Feature_88`, keras_input_1.`Feature_89` AS `Feature_89`, keras_input_1.`Feature_90` AS `Feature_90`, keras_input_1.`Feature_91` AS `Feature_91`, keras_input_1.`Feature_92` AS `Feature_92`, keras_input_1.`Feature_93` AS `Feature_93`, keras_input_1.`Feature_94` AS `Feature_94`, keras_input_1.`Feature_95` AS `Feature_95`, keras_input_1.`Feature_96` AS `Feature_96`, keras_input_1.`Feature_97` AS `Feature_97`, keras_input_1.`Feature_98` AS `Feature_98`, keras_input_1.`Feature_99` AS `Feature_99` 
  FROM keras_input_1), 
  lstm_input_kernel_bias AS 
  (SELECT keras_input_1_rn.rn AS rn, keras_input_1_rn.`KEY` AS `KEY`, keras_input_1_rn.`Feature_0` AS `Feature_0`, keras_input_1_rn.`Feature_1` AS `Feature_1`, keras_input_1_rn.`Feature_2` AS `Feature_2`, keras_input_1_rn.`Feature_3` AS `Feature_3`, keras_input_1_rn.`Feature_4` AS `Feature_4`, keras_input_1_rn.`Feature_5` AS `Feature_5`, keras_input_1_rn.`Feature_6` AS `Feature_6`, keras_input_1_rn.`Feature_7` AS `Feature_7`, keras_input_1_rn.`Feature_8` AS `Feature_8`, keras_input_1_rn.`Feature_9` AS `Feature_9`, keras_input_1_rn.`Feature_10` AS `Feature_10`, keras_input_1_rn.`Feature_11` AS `Feature_11`, keras_input_1_rn.`Feature_12` AS `Feature_12`, keras_input_1_rn.`Feature_13` AS `Feature_13`, keras_input_1_rn.`Feature_14` AS `Feature_14`, keras_input_1_rn.`Feature_15` AS `Feature_15`, keras_input_1_rn.`Feature_16` AS `Feature_16`, keras_input_1_rn.`Feature_17` AS `Feature_17`, keras_input_1_rn.`Feature_18` AS `Feature_18`, keras_input_1_rn.`Feature_19` AS `Feature_19`, keras_input_1_rn.`Feature_20` AS `Feature_20`, keras_input_1_rn.`Feature_21` AS `Feature_21`, keras_input_1_rn.`Feature_22` AS `Feature_22`, keras_input_1_rn.`Feature_23` AS `Feature_23`, keras_input_1_rn.`Feature_24` AS `Feature_24`, keras_input_1_rn.`Feature_25` AS `Feature_25`, keras_input_1_rn.`Feature_26` AS `Feature_26`, keras_input_1_rn.`Feature_27` AS `Feature_27`, keras_input_1_rn.`Feature_28` AS `Feature_28`, keras_input_1_rn.`Feature_29` AS `Feature_29`, keras_input_1_rn.`Feature_30` AS `Feature_30`, keras_input_1_rn.`Feature_31` AS `Feature_31`, keras_input_1_rn.`Feature_32` AS `Feature_32`, keras_input_1_rn.`Feature_33` AS `Feature_33`, keras_input_1_rn.`Feature_34` AS `Feature_34`, keras_input_1_rn.`Feature_35` AS `Feature_35`, keras_input_1_rn.`Feature_36` AS `Feature_36`, keras_input_1_rn.`Feature_37` AS `Feature_37`, keras_input_1_rn.`Feature_38` AS `Feature_38`, keras_input_1_rn.`Feature_39` AS `Feature_39`, keras_input_1_rn.`Feature_40` AS `Feature_40`, keras_input_1_rn.`Feature_41` AS `Feature_41`, keras_input_1_rn.`Feature_42` AS `Feature_42`, keras_input_1_rn.`Feature_43` AS `Feature_43`, keras_input_1_rn.`Feature_44` AS `Feature_44`, keras_input_1_rn.`Feature_45` AS `Feature_45`, keras_input_1_rn.`Feature_46` AS `Feature_46`, keras_input_1_rn.`Feature_47` AS `Feature_47`, keras_input_1_rn.`Feature_48` AS `Feature_48`, keras_input_1_rn.`Feature_49` AS `Feature_49`, keras_input_1_rn.`Feature_50` AS `Feature_50`, keras_input_1_rn.`Feature_51` AS `Feature_51`, keras_input_1_rn.`Feature_52` AS `Feature_52`, keras_input_1_rn.`Feature_53` AS `Feature_53`, keras_input_1_rn.`Feature_54` AS `Feature_54`, keras_input_1_rn.`Feature_55` AS `Feature_55`, keras_input_1_rn.`Feature_56` AS `Feature_56`, keras_input_1_rn.`Feature_57` AS `Feature_57`, keras_input_1_rn.`Feature_58` AS `Feature_58`, keras_input_1_rn.`Feature_59` AS `Feature_59`, keras_input_1_rn.`Feature_60` AS `Feature_60`, keras_input_1_rn.`Feature_61` AS `Feature_61`, keras_input_1_rn.`Feature_62` AS `Feature_62`, keras_input_1_rn.`Feature_63` AS `Feature_63`, keras_input_1_rn.`Feature_64` AS `Feature_64`, keras_input_1_rn.`Feature_65` AS `Feature_65`, keras_input_1_rn.`Feature_66` AS `Feature_66`, keras_input_1_rn.`Feature_67` AS `Feature_67`, keras_input_1_rn.`Feature_68` AS `Feature_68`, keras_input_1_rn.`Feature_69` AS `Feature_69`, keras_input_1_rn.`Feature_70` AS `Feature_70`, keras_input_1_rn.`Feature_71` AS `Feature_71`, keras_input_1_rn.`Feature_72` AS `Feature_72`, keras_input_1_rn.`Feature_73` AS `Feature_73`, keras_input_1_rn.`Feature_74` AS `Feature_74`, keras_input_1_rn.`Feature_75` AS `Feature_75`, keras_input_1_rn.`Feature_76` AS `Feature_76`, keras_input_1_rn.`Feature_77` AS `Feature_77`, keras_input_1_rn.`Feature_78` AS `Feature_78`, keras_input_1_rn.`Feature_79` AS `Feature_79`, keras_input_1_rn.`Feature_80` AS `Feature_80`, keras_input_1_rn.`Feature_81` AS `Feature_81`, keras_input_1_rn.`Feature_82` AS `Feature_82`, keras_input_1_rn.`Feature_83` AS `Feature_83`, keras_input_1_rn.`Feature_84` AS `Feature_84`, keras_input_1_rn.`Feature_85` AS `Feature_85`, keras_input_1_rn.`Feature_86` AS `Feature_86`, keras_input_1_rn.`Feature_87` AS `Feature_87`, keras_input_1_rn.`Feature_88` AS `Feature_88`, keras_input_1_rn.`Feature_89` AS `Feature_89`, keras_input_1_rn.`Feature_90` AS `Feature_90`, keras_input_1_rn.`Feature_91` AS `Feature_91`, keras_input_1_rn.`Feature_92` AS `Feature_92`, keras_input_1_rn.`Feature_93` AS `Feature_93`, keras_input_1_rn.`Feature_94` AS `Feature_94`, keras_input_1_rn.`Feature_95` AS `Feature_95`, keras_input_1_rn.`Feature_96` AS `Feature_96`, keras_input_1_rn.`Feature_97` AS `Feature_97`, keras_input_1_rn.`Feature_98` AS `Feature_98`, keras_input_1_rn.`Feature_99` AS `Feature_99`, 0.10065242072274447 + 0.22797302556074153 * keras_input_1_rn.`Feature_0` + 0.14961310400691435 * keras_input_1_rn.`Feature_1` + -0.15246820297058533 * keras_input_1_rn.`Feature_2` + 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keras_input_1_rn.`Feature_82` + -0.09688487193432464 * keras_input_1_rn.`Feature_83` + 0.09800326024994474 * keras_input_1_rn.`Feature_84` + 0.1625613690698563 * keras_input_1_rn.`Feature_85` + -0.15141733870811305 * keras_input_1_rn.`Feature_86` + 0.15128032399892583 * keras_input_1_rn.`Feature_87` + 0.05949378707128824 * keras_input_1_rn.`Feature_88` + -0.14919208780948273 * keras_input_1_rn.`Feature_89` + -0.18046880685479677 * keras_input_1_rn.`Feature_90` + -0.23920338237305522 * keras_input_1_rn.`Feature_91` + 0.1398000873228234 * keras_input_1_rn.`Feature_92` + -0.12088521810019953 * keras_input_1_rn.`Feature_93` + -0.04632136223223325 * keras_input_1_rn.`Feature_94` + 0.019782336931935422 * keras_input_1_rn.`Feature_95` + 0.13057903762383008 * keras_input_1_rn.`Feature_96` + 0.0436784556656729 * keras_input_1_rn.`Feature_97` + 0.22946462297081932 * keras_input_1_rn.`Feature_98` + 0.16885761005589345 * keras_input_1_rn.`Feature_99` AS dot_prod_o_2, 0.014840449900466452 + -0.04339646443281032 * keras_input_1_rn.`Feature_0` + 0.1319342046978347 * keras_input_1_rn.`Feature_1` + -0.19428594030312832 * keras_input_1_rn.`Feature_2` + -0.01906758517048845 * keras_input_1_rn.`Feature_3` + 0.28445270990911137 * keras_input_1_rn.`Feature_4` + 0.1688015611293503 * keras_input_1_rn.`Feature_5` + -0.23063777090388493 * keras_input_1_rn.`Feature_6` + -0.09967163932441019 * keras_input_1_rn.`Feature_7` + -0.022660295633618294 * keras_input_1_rn.`Feature_8` + 0.14127466770127664 * keras_input_1_rn.`Feature_9` + 0.013659345476178524 * keras_input_1_rn.`Feature_10` + 0.13930144808629738 * keras_input_1_rn.`Feature_11` + -0.06469326746891894 * keras_input_1_rn.`Feature_12` + 0.1212977296206753 * keras_input_1_rn.`Feature_13` + 0.08510947979094377 * keras_input_1_rn.`Feature_14` + -0.07579995172070737 * keras_input_1_rn.`Feature_15` + 0.089701995747099 * keras_input_1_rn.`Feature_16` + 0.13160904525649733 * keras_input_1_rn.`Feature_17` + -0.1453606199987197 * keras_input_1_rn.`Feature_18` + -0.14936421901778527 * keras_input_1_rn.`Feature_19` + 0.21069647309221406 * keras_input_1_rn.`Feature_20` + -0.23338176506884187 * keras_input_1_rn.`Feature_21` + 0.251881937904061 * keras_input_1_rn.`Feature_22` + -0.08337940278338217 * keras_input_1_rn.`Feature_23` + -0.14662702480591466 * keras_input_1_rn.`Feature_24` + -0.1772237091944507 * keras_input_1_rn.`Feature_25` + 0.1817739174492448 * keras_input_1_rn.`Feature_26` + 0.011380590841614996 * keras_input_1_rn.`Feature_27` + -0.22909809498623965 * keras_input_1_rn.`Feature_28` + -0.21728176694003315 * keras_input_1_rn.`Feature_29` + -0.19779905190179126 * keras_input_1_rn.`Feature_30` + 0.12514663737675996 * keras_input_1_rn.`Feature_31` + -0.08991930410737843 * keras_input_1_rn.`Feature_32` + 0.051053910954211135 * keras_input_1_rn.`Feature_33` + 0.14455825297487432 * keras_input_1_rn.`Feature_34` + 0.08353646404094983 * keras_input_1_rn.`Feature_35` + -0.23467590494323004 * keras_input_1_rn.`Feature_36` + 0.2539711114686589 * keras_input_1_rn.`Feature_37` + 0.21594218282104 * keras_input_1_rn.`Feature_38` + 0.05948478182898776 * keras_input_1_rn.`Feature_39` + -0.1024801105118284 * keras_input_1_rn.`Feature_40` + 0.1661339394514667 * keras_input_1_rn.`Feature_41` + 0.20426018238015634 * keras_input_1_rn.`Feature_42` + 0.05874266694930299 * keras_input_1_rn.`Feature_43` + 0.020558820337393948 * keras_input_1_rn.`Feature_44` + 0.18323922746020244 * keras_input_1_rn.`Feature_45` + -0.008773922116906122 * keras_input_1_rn.`Feature_46` + 0.038631419267683396 * keras_input_1_rn.`Feature_47` + -0.1641270785666153 * keras_input_1_rn.`Feature_48` + 0.09401436294477838 * keras_input_1_rn.`Feature_49` + -0.05383922193147752 * keras_input_1_rn.`Feature_50` + 0.05926133765090285 * keras_input_1_rn.`Feature_51` + -0.09213665640870669 * keras_input_1_rn.`Feature_52` + 0.12757141941420533 * keras_input_1_rn.`Feature_53` + -0.20128149033087195 * keras_input_1_rn.`Feature_54` + 0.21857838994336184 * keras_input_1_rn.`Feature_55` + -0.15779206353397662 * keras_input_1_rn.`Feature_56` + -0.1088726080515434 * keras_input_1_rn.`Feature_57` + 0.09793980859158843 * keras_input_1_rn.`Feature_58` + 0.09542392835948602 * keras_input_1_rn.`Feature_59` + -0.130255832011688 * keras_input_1_rn.`Feature_60` + -0.14758618462113338 * keras_input_1_rn.`Feature_61` + 0.1739476055684174 * keras_input_1_rn.`Feature_62` + 0.07718655887959856 * keras_input_1_rn.`Feature_63` + -0.19926372587052013 * keras_input_1_rn.`Feature_64` + -0.13366235247970606 * keras_input_1_rn.`Feature_65` + -0.13395374880524663 * keras_input_1_rn.`Feature_66` + 0.03759788136645025 * keras_input_1_rn.`Feature_67` + 0.172557131240991 * keras_input_1_rn.`Feature_68` + 0.1863136187912812 * keras_input_1_rn.`Feature_69` + 0.20092226374065164 * keras_input_1_rn.`Feature_70` + 0.033486995896141535 * keras_input_1_rn.`Feature_71` + 0.10142694415055002 * keras_input_1_rn.`Feature_72` + -0.24426349875136058 * keras_input_1_rn.`Feature_73` + -0.04281022335821526 * keras_input_1_rn.`Feature_74` + -0.20028222320797337 * keras_input_1_rn.`Feature_75` + 0.05842768161979031 * keras_input_1_rn.`Feature_76` + 0.20764896980286426 * keras_input_1_rn.`Feature_77` + -0.21238659199710905 * keras_input_1_rn.`Feature_78` + -0.2134998650819726 * keras_input_1_rn.`Feature_79` + 0.01143458042412161 * keras_input_1_rn.`Feature_80` + 0.11800782336030684 * keras_input_1_rn.`Feature_81` + -0.18411000848221218 * keras_input_1_rn.`Feature_82` + 0.052397361162478964 * keras_input_1_rn.`Feature_83` + 0.2245399969104817 * keras_input_1_rn.`Feature_84` + 0.08075199134864178 * keras_input_1_rn.`Feature_85` + 0.0907906288957234 * keras_input_1_rn.`Feature_86` + 0.11112232039160548 * keras_input_1_rn.`Feature_87` + -0.1509702417020474 * keras_input_1_rn.`Feature_88` + -0.22482004537764458 * keras_input_1_rn.`Feature_89` + -0.17513643948216673 * keras_input_1_rn.`Feature_90` + -0.256254007007087 * keras_input_1_rn.`Feature_91` + -0.14912589692721717 * keras_input_1_rn.`Feature_92` + -0.04389333102996395 * keras_input_1_rn.`Feature_93` + 0.10738751265552952 * keras_input_1_rn.`Feature_94` + 0.1676262714942419 * keras_input_1_rn.`Feature_95` + 0.13446271243428629 * keras_input_1_rn.`Feature_96` + -0.1766052572051065 * keras_input_1_rn.`Feature_97` + -0.1194355751769187 * keras_input_1_rn.`Feature_98` + 0.19199273857749966 * keras_input_1_rn.`Feature_99` AS dot_prod_o_3 
  FROM keras_input_1_rn), 
  rnn_cte_lstm_1(rn_1, `KEY`, `PreviousState_1`, `PreviousState_2`, `PreviousState_3`, `PreviousState_4`, `PreviousState_5`, `PreviousState_6`, `State_1`, `State_2`, `State_3`, `State_4`, `State_5`, `State_6`) AS 
  (SELECT lstm_input_kernel_bias.rn AS rn_1, lstm_input_kernel_bias.`KEY` AS `KEY`, CAST(0.0 AS DOUBLE) AS `PreviousState_1`, CAST(0.0 AS DOUBLE) AS `PreviousState_2`, CAST(0.0 AS DOUBLE) AS `PreviousState_3`, CAST(0.0 AS DOUBLE) AS `PreviousState_4`, CAST(0.0 AS DOUBLE) AS `PreviousState_5`, CAST(0.0 AS DOUBLE) AS `PreviousState_6`, greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_o_1 + 0.0) + 0.5)) * (greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_i_1 + 0.0) + 0.5)) * (lstm_input_kernel_bias.dot_prod_c_1 + 0.0) + greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_f_1 + 0.0) + 0.5)) * 0.0) AS `State_1`, greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_o_2 + 0.0) + 0.5)) * (greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_i_2 + 0.0) + 0.5)) * (lstm_input_kernel_bias.dot_prod_c_2 + 0.0) + greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_f_2 + 0.0) + 0.5)) * 0.0) AS `State_2`, greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_o_3 + 0.0) + 0.5)) * (greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_i_3 + 0.0) + 0.5)) * (lstm_input_kernel_bias.dot_prod_c_3 + 0.0) + greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_f_3 + 0.0) + 0.5)) * 0.0) AS `State_3`, greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_i_1 + 0.0) + 0.5)) * (lstm_input_kernel_bias.dot_prod_c_1 + 0.0) + greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_f_1 + 0.0) + 0.5)) * 0.0 AS `State_4`, greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_i_2 + 0.0) + 0.5)) * (lstm_input_kernel_bias.dot_prod_c_2 + 0.0) + greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_f_2 + 0.0) + 0.5)) * 0.0 AS `State_5`, greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_i_3 + 0.0) + 0.5)) * (lstm_input_kernel_bias.dot_prod_c_3 + 0.0) + greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_f_3 + 0.0) + 0.5)) * 0.0 AS `State_6` 
  FROM lstm_input_kernel_bias 
  WHERE lstm_input_kernel_bias.rn = 1 UNION ALL SELECT lstm_input_kernel_bias.rn AS rn, lstm_input_kernel_bias.`KEY` AS `KEY`, rnn_cte_lstm_1.`State_1` AS `PreviousState_1`, rnn_cte_lstm_1.`State_2` AS `PreviousState_2`, rnn_cte_lstm_1.`State_3` AS `PreviousState_3`, rnn_cte_lstm_1.`State_4` AS `PreviousState_4`, rnn_cte_lstm_1.`State_5` AS `PreviousState_5`, rnn_cte_lstm_1.`State_6` AS `PreviousState_6`, greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_o_1 + 0.0303851051522346 * rnn_cte_lstm_1.`State_1` + 0.3267297591698742 * rnn_cte_lstm_1.`State_2` + 0.3969922840576057 * rnn_cte_lstm_1.`State_3`) + 0.5)) * (greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_i_1 + 0.7386345576659287 * rnn_cte_lstm_1.`State_1` + -0.10502808735755556 * rnn_cte_lstm_1.`State_2` + -0.17326268789391955 * rnn_cte_lstm_1.`State_3`) + 0.5)) * (lstm_input_kernel_bias.dot_prod_c_1 + -0.014470725903842093 * rnn_cte_lstm_1.`State_1` + 0.24891044220379194 * rnn_cte_lstm_1.`State_2` + 0.34790590790739684 * rnn_cte_lstm_1.`State_3`) + greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_f_1 + -0.05821746804857015 * rnn_cte_lstm_1.`State_1` + 0.3702912825270262 * rnn_cte_lstm_1.`State_2` + -0.054227420953925944 * rnn_cte_lstm_1.`State_3`) + 0.5)) * rnn_cte_lstm_1.`State_4`) AS `State_1`, greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_o_2 + -0.19966852648215178 * rnn_cte_lstm_1.`State_1` + -0.34624468960173466 * rnn_cte_lstm_1.`State_2` + 0.16402565996896215 * rnn_cte_lstm_1.`State_3`) + 0.5)) * (greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_i_2 + -0.10714497383086342 * rnn_cte_lstm_1.`State_1` + -0.2359734782442619 * rnn_cte_lstm_1.`State_2` + 0.08017355769601324 * rnn_cte_lstm_1.`State_3`) + 0.5)) * (lstm_input_kernel_bias.dot_prod_c_2 + 0.14569344676661677 * rnn_cte_lstm_1.`State_1` + -0.022749853663836188 * rnn_cte_lstm_1.`State_2` + 0.31691721647353477 * rnn_cte_lstm_1.`State_3`) + greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_f_2 + -0.18961590920497248 * rnn_cte_lstm_1.`State_1` + -0.10792857834597293 * rnn_cte_lstm_1.`State_2` + 0.4123799784566473 * rnn_cte_lstm_1.`State_3`) + 0.5)) * rnn_cte_lstm_1.`State_5`) AS `State_2`, greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_o_3 + -0.192820298487659 * rnn_cte_lstm_1.`State_1` + 0.04584221035730867 * rnn_cte_lstm_1.`State_2` + -0.35759634119499917 * rnn_cte_lstm_1.`State_3`) + 0.5)) * (greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_i_3 + -0.257068066995617 * rnn_cte_lstm_1.`State_1` + 0.2829799234463606 * rnn_cte_lstm_1.`State_2` + -0.38081509541718 * rnn_cte_lstm_1.`State_3`) + 0.5)) * (lstm_input_kernel_bias.dot_prod_c_3 + 0.49329255672008465 * rnn_cte_lstm_1.`State_1` + -0.09835806124202819 * rnn_cte_lstm_1.`State_2` + -0.06196928505256485 * rnn_cte_lstm_1.`State_3`) + greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_f_3 + -0.06911346504831663 * rnn_cte_lstm_1.`State_1` + 0.5543955681940209 * rnn_cte_lstm_1.`State_2` + -0.319909359288313 * rnn_cte_lstm_1.`State_3`) + 0.5)) * rnn_cte_lstm_1.`State_6`) AS `State_3`, greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_i_1 + 0.7386345576659287 * rnn_cte_lstm_1.`State_1` + -0.10502808735755556 * rnn_cte_lstm_1.`State_2` + -0.17326268789391955 * rnn_cte_lstm_1.`State_3`) + 0.5)) * (lstm_input_kernel_bias.dot_prod_c_1 + -0.014470725903842093 * rnn_cte_lstm_1.`State_1` + 0.24891044220379194 * rnn_cte_lstm_1.`State_2` + 0.34790590790739684 * rnn_cte_lstm_1.`State_3`) + greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_f_1 + -0.05821746804857015 * rnn_cte_lstm_1.`State_1` + 0.3702912825270262 * rnn_cte_lstm_1.`State_2` + -0.054227420953925944 * rnn_cte_lstm_1.`State_3`) + 0.5)) * rnn_cte_lstm_1.`State_4` AS `State_4`, greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_i_2 + -0.10714497383086342 * rnn_cte_lstm_1.`State_1` + -0.2359734782442619 * rnn_cte_lstm_1.`State_2` + 0.08017355769601324 * rnn_cte_lstm_1.`State_3`) + 0.5)) * (lstm_input_kernel_bias.dot_prod_c_2 + 0.14569344676661677 * rnn_cte_lstm_1.`State_1` + -0.022749853663836188 * rnn_cte_lstm_1.`State_2` + 0.31691721647353477 * rnn_cte_lstm_1.`State_3`) + greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_f_2 + -0.18961590920497248 * rnn_cte_lstm_1.`State_1` + -0.10792857834597293 * rnn_cte_lstm_1.`State_2` + 0.4123799784566473 * rnn_cte_lstm_1.`State_3`) + 0.5)) * rnn_cte_lstm_1.`State_5` AS `State_5`, greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_i_3 + -0.257068066995617 * rnn_cte_lstm_1.`State_1` + 0.2829799234463606 * rnn_cte_lstm_1.`State_2` + -0.38081509541718 * rnn_cte_lstm_1.`State_3`) + 0.5)) * (lstm_input_kernel_bias.dot_prod_c_3 + 0.49329255672008465 * rnn_cte_lstm_1.`State_1` + -0.09835806124202819 * rnn_cte_lstm_1.`State_2` + -0.06196928505256485 * rnn_cte_lstm_1.`State_3`) + greatest(0.0, least(1.0, 0.2 * (lstm_input_kernel_bias.dot_prod_f_3 + -0.06911346504831663 * rnn_cte_lstm_1.`State_1` + 0.5543955681940209 * rnn_cte_lstm_1.`State_2` + -0.319909359288313 * rnn_cte_lstm_1.`State_3`) + 0.5)) * rnn_cte_lstm_1.`State_6` AS `State_6` 
  FROM lstm_input_kernel_bias, rnn_cte_lstm_1 
  WHERE lstm_input_kernel_bias.rn = rnn_cte_lstm_1.rn_1 + 1), 
  lstm_1 AS 
  (SELECT rnn_cte_lstm_1.`KEY` AS `KEY`, CAST(rnn_cte_lstm_1.`State_1` AS DOUBLE) AS output_1, CAST(rnn_cte_lstm_1.`State_2` AS DOUBLE) AS output_2, CAST(rnn_cte_lstm_1.`State_3` AS DOUBLE) AS output_3 
  FROM rnn_cte_lstm_1), 
  lstm_1_1 AS 
  (SELECT lstm_1.`KEY` AS `KEY`, lstm_1.output_1 AS output_1, lstm_1.output_2 AS output_2, lstm_1.output_3 AS output_3 
  FROM lstm_1), 
  layer_dense_1 AS 
  (SELECT lstm_1_1.`KEY` AS `KEY`, -0.12460304701468757 + -0.3833870665579449 * lstm_1_1.output_1 + 0.00018569094652252075 * lstm_1_1.output_2 + -0.3069544694343422 * lstm_1_1.output_3 AS output_1 
  FROM lstm_1_1)
   SELECT layer_dense_1.`KEY` AS `KEY`, layer_dense_1.output_1 AS `Estimator` 
  FROM layer_dense_1