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Regression _1.json
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{"paragraphs":[{"text":"%md\n## Regression Modeling to Predict Numerical Values\n\n### This notebook shows how to predict numerical values using a multiple regression (GLM) algorithm.\n\n#### By Charlie Berger\n","user":"CBERGER","dateUpdated":"2018-02-07T02:17:34+0000","config":{"colWidth":9,"editorMode":"ace/mode/markdown","editorHide":true,"graph":{"mode":"table","optionOpen":false,"keys":[],"values":[],"scatter":{},"groups":[],"height":300},"enabled":true},"settings":{"params":{},"forms":{}},"jobName":"paragraph_1464792666489_-1927519105","id":"20160601-105106_98198174","result":{"msg":"<h2>Regression Modeling to Predict Numerical Values</h2>\n<h3>This notebook shows how to predict numerical values using a multiple regression (GLM) algorithm.</h3>\n<h4>By Charlie Berger</h4>\n","code":"SUCCESS","type":"HTML"},"dateCreated":"2018-02-06T15:02:34+0000","dateStarted":"2018-02-07T02:17:34+0000","dateFinished":"2018-02-07T02:17:34+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:115"},{"text":"%md ![tiny arrow](http://www.oracle.com/technetwork/database/options/advanced-analytics/anomaly-4364384.jpg \"tiny arrow\")\n","user":"CBERGER","dateUpdated":"2018-02-07T02:17:34+0000","config":{"tableHide":false,"colWidth":3,"editorMode":"ace/mode/markdown","editorHide":true,"graph":{"mode":"table","optionOpen":false,"keys":[],"values":[],"scatter":{},"groups":[],"height":300},"enabled":true},"settings":{"params":{},"forms":{}},"jobName":"paragraph_1517929631297_2020951934","id":"20180206-150711_561256103","result":{"msg":"<p><img src=\"http://www.oracle.com/technetwork/database/options/advanced-analytics/anomaly-4364384.jpg\" alt=\"tiny arrow\" title=\"tiny arrow\" /></p>\n","code":"SUCCESS","type":"HTML"},"dateCreated":"2018-02-06T15:07:11+0000","dateStarted":"2018-02-07T02:17:34+0000","dateFinished":"2018-02-07T02:17:34+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:116"},{"text":"%md \n\n##### For more information, check the Oracle ADWC Documentation https://docs.oracle.com/en/cloud/paas/autonomous-data-warehouse-cloud/index.html, Oracle Machine Learning folder on Oracle on Github https://github.com/oracle, Oracle Advanced Analytics http://www.oracle.com/technetwork/database/options/advanced-analytics/overview/index.html and Oracle Machine Learning on Oracle Technology Network and Introducing Oracle Machine Learning blog post","user":"CBERGER","dateUpdated":"2018-02-07T02:17:34+0000","config":{"colWidth":12,"editorMode":"ace/mode/markdown","editorHide":true,"graph":{"mode":"table","optionOpen":false,"keys":[],"values":[],"scatter":{},"groups":[],"height":300},"enabled":true},"settings":{"params":{},"forms":{}},"jobName":"paragraph_1517933519727_188572403","id":"20180206-161159_598681891","result":{"msg":"<h5>For more information, check the Oracle ADWC Documentation https://docs.oracle.com/en/cloud/paas/autonomous-data-warehouse-cloud/index.html, Oracle Machine Learning folder on Oracle on Github https://github.com/oracle, Oracle Advanced Analytics http://www.oracle.com/technetwork/database/options/advanced-analytics/overview/index.html and Oracle Machine Learning on Oracle Technology Network and Introducing Oracle Machine Learning blog post</h5>\n","code":"SUCCESS","type":"HTML"},"dateCreated":"2018-02-06T16:11:59+0000","dateStarted":"2018-02-07T02:17:34+0000","dateFinished":"2018-02-07T02:17:34+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:117"},{"text":"%md \n### Given demographic, purchase, and affinity card data for a set of customers, predict customer's YRS_RESIDENCE. Since YRS_RESIDENCE is a continuous variable, we will use the Generalized Linear Model algorithm. \n#### For more information on GLM, see the Documentation at https://docs.oracle.com/en/database/oracle/oracle-database/12.2/arpls/DBMS_DATA_MINING.html#GUID-4E3665B9-B1C2-4F6B-AB69-A7F353C70F5C ","user":"CBERGER","dateUpdated":"2018-02-07T02:29:46+0000","config":{"colWidth":12,"editorHide":true,"graph":{"mode":"table","optionOpen":false,"keys":[],"values":[],"scatter":{},"groups":[],"height":300},"enabled":true,"editorMode":"ace/mode/markdown"},"settings":{"params":{},"forms":{}},"jobName":"paragraph_1517929761005_1534445434","id":"20180206-150921_501376917","result":{"msg":"<h3>Given demographic, purchase, and affinity card data for a set of customers, predict customer's YRS_RESIDENCE. Since YRS_RESIDENCE is a continuous variable, we will use the Generalized Linear Model algorithm.</h3>\n<h4>For more information on GLM, see the Documentation at https://docs.oracle.com/en/database/oracle/oracle-database/12.2/arpls/DBMS_DATA_MINING.html#GUID-4E3665B9-B1C2-4F6B-AB69-A7F353C70F5C</h4>\n","code":"SUCCESS","type":"HTML"},"dateCreated":"2018-02-06T15:09:21+0000","dateStarted":"2018-02-07T02:17:34+0000","dateFinished":"2018-02-07T02:17:34+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:118"},{"title":"Clean Up Previous Runs and Create CUSTOMERS360 table","text":"%script\n-- Drop any previously existing CUSTOMERS360 table for notebook repeatability\nBEGIN\n EXECUTE IMMEDIATE 'DROP Table CUSTOMERS360';\n EXCEPTION\n WHEN OTHERS THEN NULL;\nEND;\n/\n\n-- JOIN selected attributes from SH.CUSTOMERS and SH.SUPPLEMENTARY_DEMOGRAPHICS tables to create better 360 view of customer\nCreate table CUSTOMERS360 as SELECT a.CUST_ID, a.CUST_GENDER, a.CUST_MARITAL_STATUS, a.CUST_YEAR_OF_BIRTH, a.CUST_INCOME_LEVEL, a.CUST_CREDIT_LIMIT, b.EDUCATION, b.AFFINITY_CARD, b.HOUSEHOLD_SIZE, b.OCCUPATION, b.YRS_RESIDENCE, b.Y_BOX_GAMES\n FROM SH.CUSTOMERS a, SH.SUPPLEMENTARY_DEMOGRAPHICS b\n WHERE a.CUST_ID = b.CUST_ID;","user":"CBERGER","dateUpdated":"2018-02-07T02:17:34+0000","config":{"colWidth":12,"editorMode":"ace/mode/plsql","title":true,"graph":{"mode":"table","optionOpen":false,"keys":[],"values":[],"scatter":{},"groups":[],"height":300},"enabled":true},"settings":{"params":{},"forms":{}},"jobName":"paragraph_1517931217882_202880920","id":"20180206-153337_857542884","result":{"msg":"\nPL/SQL procedure successfully completed.\n\n---------------------------\n\nTable CUSTOMERS360 created.\n\n","code":"SUCCESS","type":"TEXT"},"dateCreated":"2018-02-06T15:33:37+0000","dateStarted":"2018-02-07T02:17:34+0000","dateFinished":"2018-02-07T02:17:35+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:119"},{"title":"Clean Up any Previous Exising Model Objects","text":"%script \n\n-- Clean up any previous GLM Models for notebook repeatability\nBEGIN\n DBMS_DATA_MINING.DROP_MODEL('GLMR_SH_Regr_sample');\nEXCEPTION WHEN OTHERS THEN NULL; \nEND;\n/\n\n-- Clean up and drop any previous GLM Model Settings table for notebook repeatability\nBEGIN EXECUTE IMMEDIATE 'DROP TABLE glmr_sh_sample_settings';\nEXCEPTION WHEN OTHERS THEN NULL; END;\n/\n\n-- Clean up and drop any previous Model Diagnostics table for notebook repeatability\nBEGIN EXECUTE IMMEDIATE 'DROP TABLE glmr_sh_sample_diag';\nEXCEPTION WHEN OTHERS THEN NULL; END;\n/","user":"CBERGER","dateUpdated":"2018-02-07T02:17:34+0000","config":{"colWidth":12,"editorMode":"ace/mode/plsql","title":true,"graph":{"mode":"table","optionOpen":false,"keys":[],"values":[],"scatter":{},"groups":[],"height":300},"enabled":true},"settings":{"params":{},"forms":{}},"jobName":"paragraph_1517945572347_-1023304399","id":"20180206-193252_591163826","result":{"msg":"\nPL/SQL procedure successfully completed.\n\n---------------------------\n\nPL/SQL procedure successfully completed.\n\n---------------------------\n\nPL/SQL procedure successfully completed.\n\n","code":"SUCCESS","type":"TEXT"},"dateCreated":"2018-02-06T19:32:52+0000","dateStarted":"2018-02-07T02:17:34+0000","dateFinished":"2018-02-07T02:17:35+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:120"},{"title":"Create GLM Model Settings table","text":"%sql\nCREATE TABLE glmr_sh_sample_settings (\n setting_name VARCHAR2(30),\n setting_value VARCHAR2(4000));","user":"CBERGER","dateUpdated":"2018-02-07T02:17:34+0000","config":{"tableHide":false,"colWidth":12,"editorMode":"ace/mode/osql","editorHide":false,"title":true,"graph":{"mode":"table","optionOpen":false,"keys":[],"values":[],"scatter":{},"groups":[],"height":300},"enabled":true},"settings":{"params":{},"forms":{}},"jobName":"paragraph_1517930865581_-204059702","id":"20180206-152745_319643522","result":{"msg":"Updated 0 row(s).","code":"SUCCESS","type":"TEXT"},"dateCreated":"2018-02-06T15:27:45+0000","dateStarted":"2018-02-07T02:17:35+0000","dateFinished":"2018-02-07T02:17:35+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:121"},{"title":"Turn on Automated Data Preparation and GLM Model Feature Selection","text":"%script \nBEGIN \n-- Populate settings table\n INSERT INTO glmr_sh_sample_settings (setting_name, setting_value) VALUES\n (dbms_data_mining.algo_name, dbms_data_mining.algo_generalized_linear_model);\n -- output row diagnostic statistics into a table named GLMC_SH_SAMPLE_DIAG \n INSERT INTO glmr_sh_sample_settings (setting_name, setting_value) VALUES\n (dbms_data_mining.glms_diagnostics_table_name, 'GLMR_SH_SAMPLE_DIAG'); \n INSERT INTO glmr_sh_sample_settings (setting_name, setting_value) VALUES\n (dbms_data_mining.prep_auto, dbms_data_mining.prep_auto_on); \n -- turn on feature selection\n INSERT INTO glmr_sh_sample_settings (setting_name, setting_value) VALUES \n (dbms_data_mining.glms_ftr_selection, \n dbms_data_mining.glms_ftr_selection_enable);\n -- turn on feature generation\n INSERT INTO glmr_sh_sample_settings (setting_name, setting_value) VALUES \n (dbms_data_mining.glms_ftr_generation, \n dbms_data_mining.glms_ftr_generation_enable); \nEND;","user":"CBERGER","dateUpdated":"2018-02-07T02:17:34+0000","config":{"colWidth":12,"title":true,"graph":{"mode":"table","optionOpen":false,"keys":[],"values":[],"scatter":{},"groups":[],"height":300},"enabled":true,"editorMode":"ace/mode/plsql"},"settings":{"params":{},"forms":{}},"jobName":"paragraph_1517930869092_1498454181","id":"20180206-152749_2147203620","result":{"msg":"\nPL/SQL procedure successfully completed.\n\n","code":"SUCCESS","type":"TEXT"},"dateCreated":"2018-02-06T15:27:49+0000","dateStarted":"2018-02-07T02:17:35+0000","dateFinished":"2018-02-07T02:17:35+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:122"},{"text":"%md\n### Examples of possible overrides are shown below. If the user does not override, then relevant settings are determined by the algorithm\n### specify a row weight column \n-- (dbms_data_mining.odms_row_weight_column_name,<row_weight_column_name>);\n-- specify a missing value treatment method:\n Default: replace with mean (numeric features) or \n mode (categorical features) \n or delete the row\n (dbms_data_mining.odms_missing_value_treatment,\n dbms_data_mining.odms_missing_value_delete_row);\n -- turn ridge regression on or off \n By default the system turns it on if there is a multicollinearity\n (dbms_data_mining.glms_ridge_regression,\n dbms_data_mining.glms_ridge_reg_enable); ","user":"CBERGER","dateUpdated":"2018-02-07T02:17:34+0000","config":{"tableHide":true,"colWidth":12,"editorHide":false,"graph":{"mode":"table","optionOpen":false,"keys":[],"values":[],"scatter":{},"groups":[],"height":300},"enabled":true,"editorMode":"ace/mode/markdown"},"settings":{"params":{},"forms":{}},"jobName":"paragraph_1517930872484_1670821689","id":"20180206-152752_1918117270","result":{"msg":"<h3>Examples of possible overrides are shown below. If the user does not override, then relevant settings are determined by the algorithm</h3>\n<h3>specify a row weight column</h3>\n<p>– (dbms_data_mining.odms_row_weight_column_name,<row_weight_column_name>);\n<br />– specify a missing value treatment method:</p>\n<pre><code> Default: replace with mean (numeric features) or \n mode (categorical features) \n or delete the row\n(dbms_data_mining.odms_missing_value_treatment,\n dbms_data_mining.odms_missing_value_delete_row);\n</code></pre>\n<p>– turn ridge regression on or off</p>\n<pre><code> By default the system turns it on if there is a multicollinearity\n(dbms_data_mining.glms_ridge_regression,\n dbms_data_mining.glms_ridge_reg_enable); \n</code></pre>\n","code":"SUCCESS","type":"HTML"},"dateCreated":"2018-02-06T15:27:52+0000","dateStarted":"2018-02-07T02:17:34+0000","dateFinished":"2018-02-07T02:17:34+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:123"},{"title":"Build the GLM Regression Model","text":"%script\n\ndeclare\n v_xlst dbms_data_mining_transform.TRANSFORM_LIST;\n \nBEGIN\n DBMS_DATA_MINING.CREATE_MODEL(\n model_name => 'GLMR_SH_Regr_sample',\n mining_function => dbms_data_mining.regression,\n data_table_name => 'CUSTOMERS360',\n case_id_column_name => 'CUST_ID',\n target_column_name => 'AFFINITY_CARD',\n settings_table_name => 'glmr_sh_sample_settings',\n xform_list => v_xlst);\nEND;","user":"CBERGER","dateUpdated":"2018-02-07T02:17:34+0000","config":{"colWidth":12,"editorMode":"ace/mode/plsql","title":true,"graph":{"mode":"table","optionOpen":false,"keys":[],"values":[],"scatter":{},"groups":[],"height":300},"enabled":true},"settings":{"params":{},"forms":{}},"jobName":"paragraph_1517931056704_1666264354","id":"20180206-153056_1655949718","result":{"msg":"\nPL/SQL procedure successfully completed.\n\n","code":"SUCCESS","type":"TEXT"},"dateCreated":"2018-02-06T15:30:56+0000","dateStarted":"2018-02-07T02:17:35+0000","dateFinished":"2018-02-07T02:17:43+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:124"},{"title":"Display GLM Model Settings","text":"%sql\n\nSELECT setting_name, setting_value\n FROM user_mining_model_settings\n WHERE model_name = 'GLMR_SH_REGR_SAMPLE'\nORDER BY setting_name;","user":"CBERGER","dateUpdated":"2018-02-07T02:18:03+0000","config":{"colWidth":12,"editorMode":"ace/mode/osql","title":true,"graph":{"mode":"table","optionOpen":false,"keys":[{"name":"SETTING_NAME","index":0,"aggr":"sum"}],"values":[{"name":"SETTING_VALUE","index":1,"aggr":"sum"}],"scatter":{"yAxis":{"name":"SETTING_VALUE","index":1,"aggr":"sum"},"xAxis":{"name":"SETTING_NAME","index":0,"aggr":"sum"}},"groups":[],"height":300},"enabled":true},"settings":{"params":{},"forms":{}},"jobName":"paragraph_1517931685837_1498052987","id":"20180206-154125_268464768","result":{"msg":"SETTING_NAME\tSETTING_VALUE\nALGO_NAME\tALGO_GENERALIZED_LINEAR_MODEL\nGLMS_CONF_LEVEL\t.95\nGLMS_DIAGNOSTICS_TABLE_NAME\tGLMR_SH_SAMPLE_DIAG\nGLMS_FTR_GENERATION\tGLMS_FTR_GENERATION_ENABLE\nGLMS_FTR_SELECTION\tGLMS_FTR_SELECTION_ENABLE\nGLMS_FTR_SEL_CRIT\tGLMS_FTR_SEL_ALPHA_INV\nGLMS_MAX_FEATURES\t1000\nGLMS_PRUNE_MODEL\tGLMS_PRUNE_MODEL_ENABLE\nGLMS_SELECT_BLOCK\tGLMS_SELECT_BLOCK_DISABLE\nODMS_MISSING_VALUE_TREATMENT\tODMS_MISSING_VALUE_AUTO\nODMS_SAMPLING\tODMS_SAMPLING_DISABLE\nPREP_AUTO\tON\n","code":"SUCCESS","type":"TABLE","comment":""},"dateCreated":"2018-02-06T15:41:25+0000","dateStarted":"2018-02-07T02:18:03+0000","dateFinished":"2018-02-07T02:18:03+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:125"},{"title":"Display GLM Model Signature","text":"%sql\n\nSELECT attribute_name, attribute_type\n FROM user_mining_model_attributes\n WHERE model_name = 'GLMR_SH_REGR_SAMPLE'\nORDER BY attribute_name;","user":"CBERGER","dateUpdated":"2018-02-07T02:18:10+0000","config":{"colWidth":12,"editorMode":"ace/mode/osql","title":true,"graph":{"mode":"table","optionOpen":false,"keys":[{"name":"ATTRIBUTE_NAME","index":0,"aggr":"sum"}],"values":[{"name":"ATTRIBUTE_TYPE","index":1,"aggr":"sum"}],"scatter":{"yAxis":{"name":"ATTRIBUTE_TYPE","index":1,"aggr":"sum"},"xAxis":{"name":"ATTRIBUTE_NAME","index":0,"aggr":"sum"}},"groups":[],"height":300},"enabled":true},"settings":{"params":{},"forms":{}},"jobName":"paragraph_1517931685840_1509210706","id":"20180206-154125_430979716","result":{"msg":"ATTRIBUTE_NAME\tATTRIBUTE_TYPE\nAFFINITY_CARD\tNUMERICAL\nCUST_GENDER\tCATEGORICAL\nCUST_INCOME_LEVEL\tCATEGORICAL\nCUST_MARITAL_STATUS\tCATEGORICAL\nCUST_YEAR_OF_BIRTH\tNUMERICAL\nEDUCATION\tCATEGORICAL\nHOUSEHOLD_SIZE\tCATEGORICAL\nOCCUPATION\tCATEGORICAL\nYRS_RESIDENCE\tNUMERICAL\nY_BOX_GAMES\tNUMERICAL\n","code":"SUCCESS","type":"TABLE","comment":""},"dateCreated":"2018-02-06T15:41:25+0000","dateStarted":"2018-02-07T02:18:10+0000","dateFinished":"2018-02-07T02:18:10+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:126"},{"title":"Show list of model views","text":"%sql \nSELECT view_name, view_type FROM user_mining_model_views\n WHERE model_name='GLMR_SH_REGR_SAMPLE'\n ORDER BY view_name;","user":"CBERGER","dateUpdated":"2018-02-07T02:18:16+0000","config":{"colWidth":12,"editorMode":"ace/mode/osql","title":true,"graph":{"mode":"table","optionOpen":false,"keys":[{"name":"VIEW_NAME","index":0,"aggr":"sum"}],"values":[{"name":"VIEW_TYPE","index":1,"aggr":"sum"}],"scatter":{"yAxis":{"name":"VIEW_TYPE","index":1,"aggr":"sum"},"xAxis":{"name":"VIEW_NAME","index":0,"aggr":"sum"}},"groups":[],"height":209},"enabled":true},"settings":{"params":{},"forms":{}},"jobName":"paragraph_1517969477343_790092446","id":"20180207-021117_501165555","result":{"msg":"VIEW_NAME\tVIEW_TYPE\nDM$VAGLMR_SH_REGR_SAMPLE\tGLM Regression Row Diagnostics\nDM$VDGLMR_SH_REGR_SAMPLE\tGLM Regression Attribute Diagnostics\nDM$VGGLMR_SH_REGR_SAMPLE\tGlobal Name-Value Pairs\nDM$VSGLMR_SH_REGR_SAMPLE\tComputed Settings\nDM$VWGLMR_SH_REGR_SAMPLE\tModel Build Alerts\n","code":"SUCCESS","type":"TABLE","comment":""},"dateCreated":"2018-02-07T02:11:17+0000","dateStarted":"2018-02-07T02:18:16+0000","dateFinished":"2018-02-07T02:18:16+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:127"},{"title":"Show global GLM model statistics","text":"%sql \nselect name, numeric_value, string_value from DM$VGGLMR_SH_REGR_SAMPLE\n ORDER BY name;","user":"CBERGER","dateUpdated":"2018-02-07T02:18:21+0000","config":{"colWidth":12,"editorMode":"ace/mode/osql","title":true,"graph":{"mode":"table","optionOpen":false,"keys":[{"name":"NAME","index":0,"aggr":"sum"}],"values":[{"name":"NUMERIC_VALUE","index":1,"aggr":"sum"}],"scatter":{"yAxis":{"name":"NUMERIC_VALUE","index":1,"aggr":"sum"},"xAxis":{"name":"NAME","index":0,"aggr":"sum"}},"groups":[],"height":300},"enabled":true},"settings":{"params":{},"forms":{}},"jobName":"paragraph_1517969584924_-1383784812","id":"20180207-021304_1710507199","result":{"msg":"NAME\tNUMERIC_VALUE\tSTRING_VALUE\nADJUSTED_R_SQUARE\t0.35225488814328065\t\nAIC\t-9596.2466513098807\t\nCOEFF_VAR\t143.93729819312802\t\nCONVERGED\t\tYES\nCORRECTED_TOTAL_DF\t4499\t\nCORRECTED_TOT_SS\t816.62577777777778\t\nDEPENDENT_MEAN\t0.23822222222222222\t\nERROR_DF\t4463\t\nERROR_MEAN_SQUARE\t0.11757398439025274\t\nERROR_SUM_SQUARES\t524.73269233369797\t\nF_VALUE\t68.962035303855373\t\nGMSEP\t0.11854892503734712\t\nHOCKING_SP\t0.000026350063736049472\t\nJ_P\t0.11854070381746148\t\nMODEL_DF\t36\t\nMODEL_F_P_VALUE\t0\t\nMODEL_MEAN_SQUARE\t8.1081412623355504\t\nMODEL_SUM_SQUARES\t291.89308544407982\t\nNUM_PARAMS\t37\t\nNUM_ROWS\t4500\t\nROOT_MEAN_SQ\t0.34289063036229606\t\nR_SQ\t0.35743800084095612\t\nSBIC\t-9359.0088423068191\t\nVALID_COVARIANCE_MATRIX\t\tYES\n","code":"SUCCESS","type":"TABLE","comment":""},"dateCreated":"2018-02-07T02:13:04+0000","dateStarted":"2018-02-07T02:18:21+0000","dateFinished":"2018-02-07T02:18:21+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:128"},{"title":"Show model coefficient statistics","text":"%sql \nSELECT feature_expression, coefficient, std_error, test_statistic,\n p_value, std_coefficient, lower_coeff_limit, upper_coeff_limit\n FROM DM$VDGLMR_SH_REGR_SAMPLE\n ORDER BY 1;","user":"CBERGER","dateUpdated":"2018-02-07T02:18:27+0000","config":{"colWidth":12,"editorMode":"ace/mode/osql","title":true,"graph":{"mode":"table","optionOpen":false,"keys":[{"name":"FEATURE_EXPRESSION","index":0,"aggr":"sum"}],"values":[{"name":"COEFFICIENT","index":1,"aggr":"sum"}],"scatter":{"yAxis":{"name":"COEFFICIENT","index":1,"aggr":"sum"},"xAxis":{"name":"FEATURE_EXPRESSION","index":0,"aggr":"sum"}},"groups":[],"height":300},"enabled":true},"settings":{"params":{},"forms":{}},"jobName":"paragraph_1517969683225_1525087084","id":"20180207-021443_894730855","result":{"msg":"FEATURE_EXPRESSION\tCOEFFICIENT\tSTD_ERROR\tTEST_STATISTIC\tP_VALUE\tSTD_COEFFICIENT\tLOWER_COEFF_LIMIT\tUPPER_COEFF_LIMIT\nCUST_GENDER_F*OCCUPATION_Other\t0.1390493772546173\t0.03318988466250224\t4.189510709921645\t2.849577903919754E-5\t0.07546753874300811\t0.0739807574072209\t0.2041179971020137\nCUST_INCOME_LEVEL_B: 30,000 - 49,999\t0.0637078430454677\t0.02393657913191801\t2.66152664064336\t0.007806587103769777\t0.03238709382852519\t0.01678028714041291\t0.11063539895052249\nCUST_INCOME_LEVEL_H: 150,000 - 169,999\t0.06169105006550053\t0.018633039631433607\t3.3108419928130686\t9.375484183688122E-4\t0.04041049625546339\t0.025161059536518156\t0.09822104059448292\nCUST_INCOME_LEVEL_I: 170,000 - 189,999\t0.05571329905945887\t0.01683238212341436\t3.309887967785615\t9.407417809681247E-4\t0.04051917642769086\t0.022713489489406984\t0.08871310862951076\nCUST_MARITAL_STATUS_Mar-AF\t-0.46747731494607403\t0.20080585321652336\t-2.328006417432495\t0.01995622954617016\t-0.028324666999180344\t-0.8611562884930992\t-0.07379834139904878\nCUST_MARITAL_STATUS_NeverM\t-5.057473954942552\t2.3184041097480055\t-2.1814462516167055\t0.029202430763790595\t-5.599364214205839\t-9.602694801710664\t-0.5122531081744395\nCUST_MARITAL_STATUS_NeverM*EDUCATION_Bach.\t-0.2277216509974055\t0.030489598829067273\t-7.46883067481711\t9.677394993269047E-14\t-0.12495064044029347\t-0.28749637259351934\t-0.16794692940129163\nCUST_MARITAL_STATUS_NeverM*OCCUPATION_Exec.\t-0.11964378962132534\t0.03879703430284941\t-3.083838540012792\t0.0020559756045832804\t-0.04450785131508171\t-0.19570520116068624\t-0.043582378081964426\nCUST_YEAR_OF_BIRTH*CUST_MARITAL_STATUS_NeverM\t0.002578031600949237\t0.001177126896593099\t2.1901050841763183\t0.028568186481851804\t5.637201279500195\t2.7027960586329574E-4\t0.004885783596035179\nCUST_YEAR_OF_BIRTH*OCCUPATION_Other\t0.004503440558428085\t0.0011589246624403953\t3.885878611768435\t1.0343891836443485E-4\t6.3536489729142644\t0.0022313739616645336\t0.0067755071551916365\nEDUCATION_7th-8th\t-0.10319954027270264\t0.037854578481753595\t-2.7262102607336174\t0.006431635053138441\t-0.0333569668503069\t-0.17741327140674013\t-0.02898580913866515\nEDUCATION_< Bach.\t0.05673965007647117\t0.013326761129735047\t4.257572378173123\t2.1090620112989085E-5\t0.05616548320248719\t0.030612594723142553\t0.08286670542979979\nEDUCATION_Assoc-A\t0.130554686230987\t0.02749271373860606\t4.748701327641526\t2.1114508637608196E-6\t0.05876009855550423\t0.07665534439772798\t0.18445402806424605\nEDUCATION_Bach.\t0.2576782958804407\t0.019459158535519668\t13.242006092405747\t2.7412485651395168E-39\t0.22885405091399708\t0.21952870294954174\t0.2958278888113397\nEDUCATION_Bach.*CUST_MARITAL_STATUS_Divorc.\t-0.19977981892235888\t0.0462442102548918\t-4.320104458940906\t1.593454826054788E-5\t-0.05803429312453146\t-0.29044138547544274\t-0.10911825236927501\nEDUCATION_Masters\t0.27046135890470174\t0.03181728556727827\t8.500453576808303\t2.542431639853867E-17\t0.12767411673132692\t0.208083713420073\t0.33283900438933045\nEDUCATION_PhD\t0.4248797248391367\t0.0500415724273542\t8.49053505374833\t2.7653338483349967E-17\t0.10350826880839431\t0.32677344679833864\t0.5229860028799348\nEDUCATION_Profsc\t0.38127324465774404\t0.03662348637241931\t10.410621227608637\t4.2885237355558085E-25\t0.12799844812197766\t0.30947306407605013\t0.45307342523943794\nHOUSEHOLD_SIZE_1\t-0.25812874723458445\t0.02372129284722201\t-10.881731821999482\t3.087765799802858E-27\t-0.21858486686536024\t-0.30463423534519857\t-0.21162325912397034\nHOUSEHOLD_SIZE_2\t-0.24144462272372383\t0.018699121587211376\t-12.912083682521837\t1.7903802583707386E-37\t-0.24714223310511055\t-0.2781041666302789\t-0.20478507881716873\nHOUSEHOLD_SIZE_4-5\t0.09860183732122192\t0.03198650408040489\t3.0826074982550518\t0.0020644803825177\t0.049803731096020605\t0.03589243970145492\t0.16131123494098892\nHOUSEHOLD_SIZE_4-5*CUST_INCOME_LEVEL_E: 90,000 - 109,999\t0.3513552876651068\t0.07012014110826567\t5.010761275032425\t5.63117590890945E-7\t0.06485726154167544\t0.21388506588472334\t0.4888255094454903\nHOUSEHOLD_SIZE_6-8\t-0.27591225021784316\t0.03269019274657448\t-8.440214848435094\t4.229584829293466E-17\t-0.1155123674418215\t-0.34000122630784335\t-0.21182327412784296\nHOUSEHOLD_SIZE_9+\t-0.26994197513400536\t0.0218625494604128\t-12.347232221145925\t1.8310991491437213E-34\t-0.20001229947959864\t-0.31280340518114585\t-0.22708054508686484\nOCCUPATION_Cleric.\t0.04605764234753561\t0.017861344408096846\t2.578621255780551\t0.009951291530994923\t0.03456424792177993\t0.011040556838740959\t0.08107472785633026\nOCCUPATION_Exec.\t0.15055543182673445\t0.01986416976602045\t7.579246130098718\t4.201389557269297E-14\t0.11657025618981887\t0.1116118161970716\t0.18949904745639728\nOCCUPATION_Exec.*EDUCATION_Masters\t0.1513712362333609\t0.06105804842776463\t2.479136496025454\t0.01320675254789818\t0.03650259626777341\t0.03166720646133918\t0.2710752660053826\nOCCUPATION_Farming\t-0.09428700305847335\t0.03228029608212182\t-2.9208840841671657\t0.003507890124706174\t-0.03594610399472183\t-0.1575723785783842\t-0.03100162753856249\nOCCUPATION_Other\t-8.97281661965676\t2.281460920853916\t-3.9329258448566247\t8.519190988731266E-5\t-6.429751389585221\t-13.445610510485013\t-4.500022728828506\nOCCUPATION_Sales\t0.04551679481740243\t0.0168452100244778\t2.702061580191752\t0.0069171629334771265\t0.03526923157398349\t0.012491836204917138\t0.07854175342988773\nOCCUPATION_Sales*EDUCATION_Masters\t0.30088780570799323\t0.10155044491075597\t2.962939315257731\t0.0030632552709276345\t0.0379084911464156\t0.1017986144551731\t0.4999769969608133\nOCCUPATION_TechSup\t0.06253949861632575\t0.027322616744665972\t2.288927857853694\t0.022130045087190423\t0.028537494894078475\t0.008973631175895107\t0.11610536605675639\nYRS_RESIDENCE*CUST_GENDER_F\t-0.016895238333720215\t0.0036965151496187575\t-4.570585443282361\t4.995065238855756E-6\t-0.07621587936946016\t-0.024142239685985556\t-0.009648236981454872\nYRS_RESIDENCE*YRS_RESIDENCE*YRS_RESIDENCE\t1.462020904943652E-4\t3.1978639406318777E-5\t4.571867134080652\t4.964744333344834E-6\t0.06110315246188338\t8.350811153282908E-5\t2.0889606945590134E-4\nY_BOX_GAMES\t-0.1405716844017266\t0.017585356810385713\t-7.993678258419331\t1.6543759825389997E-15\t-0.15294414800129785\t-0.17504769746448318\t-0.10609567133897004\nY_BOX_GAMES*HOUSEHOLD_SIZE_4-5\t-0.20417111535663912\t0.06690214386467727\t-3.0517873353896596\t0.0022882140577332624\t-0.04150260145145462\t-0.33533246799082783\t-0.07300976272245041\n\t0.3008235582491606\t0.013047628197589062\t23.055803989321735\t3.210832685417467E-111\t0.0\t0.27524374175590605\t0.3264033747424152\n","code":"SUCCESS","type":"TABLE","comment":""},"dateCreated":"2018-02-07T02:14:43+0000","dateStarted":"2018-02-07T02:18:27+0000","dateFinished":"2018-02-07T02:18:27+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:129"},{"title":"Show Model Features and p-values","text":"%sql \nSELECT feature_expression, coefficient, p_value \n FROM DM$VDGLMR_SH_REGR_SAMPLE\n ORDER BY feature_expression;","user":"CBERGER","dateUpdated":"2018-02-07T02:19:22+0000","config":{"colWidth":12,"editorMode":"ace/mode/osql","title":true,"graph":{"mode":"table","optionOpen":false,"keys":[{"name":"FEATURE_EXPRESSION","index":0,"aggr":"sum"}],"values":[{"name":"COEFFICIENT","index":1,"aggr":"sum"}],"scatter":{"yAxis":{"name":"COEFFICIENT","index":1,"aggr":"sum"},"xAxis":{"name":"FEATURE_EXPRESSION","index":0,"aggr":"sum"}},"groups":[],"height":300},"enabled":true},"settings":{"params":{},"forms":{}},"jobName":"paragraph_1517969780978_1506908651","id":"20180207-021620_1723314988","result":{"msg":"FEATURE_EXPRESSION\tCOEFFICIENT\tP_VALUE\nCUST_GENDER_F*OCCUPATION_Other\t0.1390493772546173\t2.849577903919754E-5\nCUST_INCOME_LEVEL_B: 30,000 - 49,999\t0.0637078430454677\t0.007806587103769777\nCUST_INCOME_LEVEL_H: 150,000 - 169,999\t0.06169105006550053\t9.375484183688122E-4\nCUST_INCOME_LEVEL_I: 170,000 - 189,999\t0.05571329905945887\t9.407417809681247E-4\nCUST_MARITAL_STATUS_Mar-AF\t-0.46747731494607403\t0.01995622954617016\nCUST_MARITAL_STATUS_NeverM\t-5.057473954942552\t0.029202430763790595\nCUST_MARITAL_STATUS_NeverM*EDUCATION_Bach.\t-0.2277216509974055\t9.677394993269047E-14\nCUST_MARITAL_STATUS_NeverM*OCCUPATION_Exec.\t-0.11964378962132534\t0.0020559756045832804\nCUST_YEAR_OF_BIRTH*CUST_MARITAL_STATUS_NeverM\t0.002578031600949237\t0.028568186481851804\nCUST_YEAR_OF_BIRTH*OCCUPATION_Other\t0.004503440558428085\t1.0343891836443485E-4\nEDUCATION_7th-8th\t-0.10319954027270264\t0.006431635053138441\nEDUCATION_< Bach.\t0.05673965007647117\t2.1090620112989085E-5\nEDUCATION_Assoc-A\t0.130554686230987\t2.1114508637608196E-6\nEDUCATION_Bach.\t0.2576782958804407\t2.7412485651395168E-39\nEDUCATION_Bach.*CUST_MARITAL_STATUS_Divorc.\t-0.19977981892235888\t1.593454826054788E-5\nEDUCATION_Masters\t0.27046135890470174\t2.542431639853867E-17\nEDUCATION_PhD\t0.4248797248391367\t2.7653338483349967E-17\nEDUCATION_Profsc\t0.38127324465774404\t4.2885237355558085E-25\nHOUSEHOLD_SIZE_1\t-0.25812874723458445\t3.087765799802858E-27\nHOUSEHOLD_SIZE_2\t-0.24144462272372383\t1.7903802583707386E-37\nHOUSEHOLD_SIZE_4-5\t0.09860183732122192\t0.0020644803825177\nHOUSEHOLD_SIZE_4-5*CUST_INCOME_LEVEL_E: 90,000 - 109,999\t0.3513552876651068\t5.63117590890945E-7\nHOUSEHOLD_SIZE_6-8\t-0.27591225021784316\t4.229584829293466E-17\nHOUSEHOLD_SIZE_9+\t-0.26994197513400536\t1.8310991491437213E-34\nOCCUPATION_Cleric.\t0.04605764234753561\t0.009951291530994923\nOCCUPATION_Exec.\t0.15055543182673445\t4.201389557269297E-14\nOCCUPATION_Exec.*EDUCATION_Masters\t0.1513712362333609\t0.01320675254789818\nOCCUPATION_Farming\t-0.09428700305847335\t0.003507890124706174\nOCCUPATION_Other\t-8.97281661965676\t8.519190988731266E-5\nOCCUPATION_Sales\t0.04551679481740243\t0.0069171629334771265\nOCCUPATION_Sales*EDUCATION_Masters\t0.30088780570799323\t0.0030632552709276345\nOCCUPATION_TechSup\t0.06253949861632575\t0.022130045087190423\nYRS_RESIDENCE*CUST_GENDER_F\t-0.016895238333720215\t4.995065238855756E-6\nYRS_RESIDENCE*YRS_RESIDENCE*YRS_RESIDENCE\t1.462020904943652E-4\t4.964744333344834E-6\nY_BOX_GAMES\t-0.1405716844017266\t1.6543759825389997E-15\nY_BOX_GAMES*HOUSEHOLD_SIZE_4-5\t-0.20417111535663912\t0.0022882140577332624\n\t0.3008235582491606\t3.210832685417467E-111\n","code":"SUCCESS","type":"TABLE","comment":""},"dateCreated":"2018-02-07T02:16:20+0000","dateStarted":"2018-02-07T02:19:22+0000","dateFinished":"2018-02-07T02:19:22+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:130"},{"title":"Create Train and Test datasets","text":"%script\n-- Split the Data into N1_TRAIN_DATA and N1_TEST_DATA\nBEGIN\nEXECUTE IMMEDIATE 'CREATE OR REPLACE VIEW N1_TRAIN_DATA AS SELECT * FROM CUSTOMERS360 SAMPLE (60) SEED (1)';\nDBMS_OUTPUT.PUT_LINE ('Created N1_TRAIN_DATA');\nEXECUTE IMMEDIATE 'CREATE OR REPLACE VIEW N1_TEST_DATA AS SELECT * FROM CUSTOMERS360 MINUS SELECT * FROM N1_TRAIN_DATA';\nDBMS_OUTPUT.PUT_LINE ('Created N1_TEST_DATA');\nEND;\n/\n","user":"CBERGER","dateUpdated":"2018-02-07T02:24:21+0000","config":{"colWidth":12,"editorMode":"ace/mode/plsql","title":true,"graph":{"mode":"table","optionOpen":false,"keys":[],"values":[],"scatter":{},"groups":[],"height":300},"enabled":true},"settings":{"params":{},"forms":{}},"jobName":"paragraph_1517970145860_1087113140","id":"20180207-022225_1868521516","result":{"msg":"Created N1_TRAIN_DATA\nCreated N1_TEST_DATA\n\n\nPL/SQL procedure successfully completed.\n\n","code":"SUCCESS","type":"TEXT"},"dateCreated":"2018-02-07T02:22:25+0000","dateStarted":"2018-02-07T02:24:22+0000","dateFinished":"2018-02-07T02:24:27+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:131"},{"title":"Score the model to make predictions","text":"%sql\n\n-- Make predictions with upper and lower bounds with Prediction_Details\n\nSELECT CUST_ID,\n PREDICTION(GLMR_SH_Regr_sample USING *) pr,\n PREDICTION_BOUNDS(GLMR_SH_Regr_sample USING *).lower pl,\n PREDICTION_BOUNDS(GLMR_SH_Regr_sample USING *).upper pu,\n PREDICTION_DETAILS(GLMR_SH_Regr_sample USING *) pd\n FROM N1_TEST_DATA\n WHERE CUST_ID < 100010\n ORDER BY CUST_ID;","user":"CBERGER","dateUpdated":"2018-02-07T02:29:17+0000","config":{"colWidth":12,"editorMode":"ace/mode/osql","title":true,"graph":{"mode":"table","optionOpen":false,"keys":[{"name":"CUST_ID","index":0,"aggr":"sum"}],"values":[{"name":"PR","index":1,"aggr":"sum"}],"scatter":{"yAxis":{"name":"PR","index":1,"aggr":"sum"},"xAxis":{"name":"CUST_ID","index":0,"aggr":"sum"}},"groups":[],"height":300},"enabled":true},"settings":{"params":{},"forms":{}},"jobName":"paragraph_1517931856838_1241454475","id":"20180206-154416_2021445758","result":{"msg":"CUST_ID\tPR\tPL\tPU\tPD\n100001\t0.21993575887082967\t0.17128049778791826\t0.26859101995374096\t<Details algorithm=\"Generalized Linear Model\">\n<Attribute name=\"OCCUPATION\" actualValue=\"Exec.\" weight=\".269\" rank=\"1\"/>\n<Attribute name=\"EDUCATION\" actualValue=\"< Bach.\" weight=\".161\" rank=\"2\"/>\n<Attribute name=\"Y_BOX_GAMES\" actualValue=\"0\" weight=\".146\" rank=\"3\"/>\n<Attribute name=\"YRS_RESIDENCE\" actualValue=\"3\" weight=\".108\" rank=\"4\"/>\n<Attribute name=\"CUST_YEAR_OF_BIRTH\" actualValue=\"1941\" weight=\".094\" rank=\"5\"/>\n</Details>\n\n100002\t0.031735606985082876\t-0.02155248919313521\t0.085023703163301004\t<Details algorithm=\"Generalized Linear Model\">\n<Attribute name=\"Y_BOX_GAMES\" actualValue=\"0\" weight=\".221\" rank=\"1\"/>\n<Attribute name=\"EDUCATION\" actualValue=\"Bach.\" weight=\".211\" rank=\"2\"/>\n<Attribute name=\"YRS_RESIDENCE\" actualValue=\"4\" weight=\".19\" rank=\"3\"/>\n<Attribute name=\"CUST_YEAR_OF_BIRTH\" actualValue=\"1962\" weight=\".185\" rank=\"4\"/>\n<Attribute name=\"CUST_GENDER\" actualValue=\"F\" weight=\".143\" rank=\"5\"/>\n</Details>\n\n100003\t0.21188529929258981\t0.16472768132096208\t0.25904291726421758\t<Details algorithm=\"Generalized Linear Model\">\n<Attribute name=\"EDUCATION\" actualValue=\"< Bach.\" weight=\".165\" rank=\"1\"/>\n<Attribute name=\"OCCUPATION\" actualValue=\"Sales\" weight=\".151\" rank=\"2\"/>\n<Attribute name=\"Y_BOX_GAMES\" actualValue=\"0\" weight=\".15\" rank=\"3\"/>\n<Attribute name=\"YRS_RESIDENCE\" actualValue=\"6\" weight=\".125\" rank=\"4\"/>\n<Attribute name=\"CUST_MARITAL_STATUS\" actualValue=\"NeverM\" weight=\".122\" rank=\"5\"/>\n</Details>\n\n100007\t-0.00033542103918030725\t-0.052713406267307313\t0.052042564188946698\t<Details algorithm=\"Generalized Linear Model\">\n<Attribute name=\"CUST_GENDER\" actualValue=\"F\" weight=\".182\" rank=\"1\"/>\n<Attribute name=\"Y_BOX_GAMES\" actualValue=\"0\" weight=\".176\" rank=\"2\"/>\n<Attribute name=\"OCCUPATION\" actualValue=\"Other\" weight=\".157\" rank=\"3\"/>\n<Attribute name=\"CUST_MARITAL_STATUS\" actualValue=\"Divorc.\" weight=\".154\" rank=\"4\"/>\n<Attribute name=\"CUST_YEAR_OF_BIRTH\" actualValue=\"1963\" weight=\".15\" rank=\"5\"/>\n</Details>\n\n","code":"SUCCESS","type":"TABLE","comment":"100002\t0.031735606985082876\t-0.02155248919313521\t0.085023703163301004\t<Details algorithm=\"Generalized Linear Model\"><Attribute name=\"Y_BOX_GAMES\" actualValue=\"0\" weight=\".221\" rank=\"1\"/><Attribute name=\"EDUCATION\" actualValue=\"Bach.\" weight=\".211\" rank=\"2\"/><Attribute name=\"YRS_RESIDENCE\" actualValue=\"4\" weight=\".19\" rank=\"3\"/><Attribute name=\"CUST_YEAR_OF_BIRTH\" actualValue=\"1962\" weight=\".185\" rank=\"4\"/><Attribute name=\"CUST_GENDER\" actualValue=\"F\" weight=\".143\" rank=\"5\"/></Details>100003\t0.21188529929258981\t0.16472768132096208\t0.25904291726421758\t<Details algorithm=\"Generalized Linear Model\"><Attribute name=\"EDUCATION\" actualValue=\"< Bach.\" weight=\".165\" rank=\"1\"/><Attribute name=\"OCCUPATION\" actualValue=\"Sales\" weight=\".151\" rank=\"2\"/><Attribute name=\"Y_BOX_GAMES\" actualValue=\"0\" weight=\".15\" rank=\"3\"/><Attribute name=\"YRS_RESIDENCE\" actualValue=\"6\" weight=\".125\" rank=\"4\"/><Attribute name=\"CUST_MARITAL_STATUS\" actualValue=\"NeverM\" weight=\".122\" rank=\"5\"/></Details>100007\t-0.00033542103918030725\t-0.052713406267307313\t0.052042564188946698\t<Details algorithm=\"Generalized Linear Model\"><Attribute name=\"CUST_GENDER\" actualValue=\"F\" weight=\".182\" rank=\"1\"/><Attribute name=\"Y_BOX_GAMES\" actualValue=\"0\" weight=\".176\" rank=\"2\"/><Attribute name=\"OCCUPATION\" actualValue=\"Other\" weight=\".157\" rank=\"3\"/><Attribute name=\"CUST_MARITAL_STATUS\" actualValue=\"Divorc.\" weight=\".154\" rank=\"4\"/><Attribute name=\"CUST_YEAR_OF_BIRTH\" actualValue=\"1963\" weight=\".15\" rank=\"5\"/></Details>"},"dateCreated":"2018-02-06T15:44:16+0000","dateStarted":"2018-02-07T02:29:17+0000","dateFinished":"2018-02-07T02:29:17+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:132"},{"text":"%script ","user":"CBERGER","dateUpdated":"2018-02-07T02:20:34+0000","config":{"colWidth":12,"graph":{"mode":"table","height":300,"optionOpen":false,"keys":[],"values":[],"groups":[],"scatter":{}},"enabled":true,"editorMode":"ace/mode/plsql"},"settings":{"params":{},"forms":{}},"jobName":"paragraph_1517970034903_2016865697","id":"20180207-022034_2057675696","dateCreated":"2018-02-07T02:20:34+0000","status":"READY","progressUpdateIntervalMs":500,"commited":false,"$$hashKey":"object:133"}],"name":"Regression _1","id":"622","angularObjects":{"ORA32A881B886:shared_process":[],"ORA861F047A1D:shared_process":[],"ORA548C38603D:shared_process":[],"MDWCF4DF17A97:shared_process":[]},"config":{"looknfeel":"default"},"info":{}}