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Feb 21, 2023
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Enhancements and Updates to almost all OML4SQL Notebooks #254

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1,706 changes: 1,706 additions & 0 deletions machine-learning/notebooks/sql/OML4SQL Anomaly Detection MSET.json
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245 changes: 73 additions & 172 deletions machine-learning/notebooks/sql/OML4SQL Anomaly Detection SVM.json
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387 changes: 153 additions & 234 deletions machine-learning/notebooks/sql/OML4SQL Association Rules Apriori.json
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112 changes: 55 additions & 57 deletions machine-learning/notebooks/sql/OML4SQL Attribute Importance MDL.json
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671 changes: 135 additions & 536 deletions machine-learning/notebooks/sql/OML4SQL Classification DT.json
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768 changes: 185 additions & 583 deletions machine-learning/notebooks/sql/OML4SQL Classification GLM.json
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638 changes: 124 additions & 514 deletions machine-learning/notebooks/sql/OML4SQL Classification NB.json
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667 changes: 171 additions & 496 deletions machine-learning/notebooks/sql/OML4SQL Classification NN.json
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985 changes: 452 additions & 533 deletions machine-learning/notebooks/sql/OML4SQL Classification RF.json
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678 changes: 143 additions & 535 deletions machine-learning/notebooks/sql/OML4SQL Classification SVM.json
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2,276 changes: 2,276 additions & 0 deletions machine-learning/notebooks/sql/OML4SQL Classification XGBoost.json
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299 changes: 144 additions & 155 deletions machine-learning/notebooks/sql/OML4SQL Clustering EM.json
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303 changes: 150 additions & 153 deletions machine-learning/notebooks/sql/OML4SQL Clustering KM.json
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288 changes: 147 additions & 141 deletions machine-learning/notebooks/sql/OML4SQL Clustering OC.json
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63 changes: 32 additions & 31 deletions machine-learning/notebooks/sql/OML4SQL Data Cleaning Duplicates Removal.json
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@@ -1,9 +1,9 @@
{
"paragraphs": [
{
"text": "%md\n\n## OML4SQL Data Cleaning: Duplicates Removal\nIn this notebook, we demonstrate how to remove duplicate records using Oracle SQL.\n\nWe use the customer insurance lifetime value data set which contains customer financial information, lifetime value, and whether or not the customer bought insurance.\n\nThe dataset `CUSTOMER_INSURANCE_LTV_SQL` is generated by the `\"OML Run-me-first\"` notebook, which `MUST` be run before this notebook.\n\n---\n\n##### `IMPORTANT`: The `\"OML Run-me-first\"` notebook is available under the menu Templates -\u003e Examples and is a pre-requisite to the current notebook.\n\n---\nCopyright (c) 2022 Oracle Corporation \n###### \u003ca href\u003d\"https://oss.oracle.com/licenses/upl/\" onclick\u003d\"return ! window.open(\u0027https://oss.oracle.com/licenses/upl/\u0027);\"\u003eThe Universal Permissive License (UPL), Version 1.0\u003c/a\u003e\n---",
"text": "%md\n\n## OML4SQL Data Cleaning: Duplicates Removal\nIn this notebook, we demonstrate how to remove duplicate records using Oracle SQL.\n\nWe use the customer insurance lifetime value data set which contains customer financial information, lifetime value, and whether or not the customer bought insurance.\n\nThe dataset `CUSTOMER_INSURANCE_LTV_SQL` is generated by the `\"OML Run-me-first\"` notebook, which `MUST` be run before this notebook.\n\n---\n\n##### `IMPORTANT`: The `\"OML Run-me-first\"` notebook is available under the menu Templates -\u003e Examples and is a pre-requisite to the current notebook.\n\n---\nCopyright (c) 2023 Oracle Corporation \n###### \u003ca href\u003d\"https://oss.oracle.com/licenses/upl/\" onclick\u003d\"return ! window.open(\u0027https://oss.oracle.com/licenses/upl/\u0027);\"\u003eThe Universal Permissive License (UPL), Version 1.0\u003c/a\u003e\n---",
"user": "OMLUSER",
"dateUpdated": "2022-03-10T18:04:40+0000",
"dateUpdated": "2023-02-17T22:48:27+0000",
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Expand All @@ -26,7 +26,7 @@
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"data": "\u003ch2\u003eOML4SQL Data Cleaning: Duplicates Removal\u003c/h2\u003e\n\u003cp\u003eIn this notebook, we demonstrate how to remove duplicate records using Oracle SQL.\u003c/p\u003e\n\u003cp\u003eWe use the customer insurance lifetime value data set which contains customer financial information, lifetime value, and whether or not the customer bought insurance.\u003c/p\u003e\n\u003cp\u003eThe dataset \u003ccode\u003eCUSTOMER_INSURANCE_LTV_SQL\u003c/code\u003e is generated by the \u003ccode\u003e\"OML Run-me-first\"\u003c/code\u003e notebook, which \u003ccode\u003eMUST\u003c/code\u003e be run before this notebook.\u003c/p\u003e\n\u003chr /\u003e\n\u003ch5\u003e\u003ccode\u003eIMPORTANT\u003c/code\u003e: The \u003ccode\u003e\"OML Run-me-first\"\u003c/code\u003e notebook is available under the menu Templates -\u003e Examples and is a pre-requisite to the current notebook.\u003c/h5\u003e\n\u003chr /\u003e\n\u003cp\u003eCopyright (c) 2022 Oracle Corporation\u003c/p\u003e\n\u003ch6\u003e\u003ca href\u003d\"https: //oss.oracle.com/licenses/upl/\" onclick\u003d\"return ! window.open(\u0027https://oss.oracle.com/licenses/upl/\u0027);\"\u003eThe Universal Permissive License (UPL), Version 1.0\u003c/a\u003e\u003c/h6\u003e\n\u003chr /\u003e\n"
"data": "\u003ch2\u003eOML4SQL Data Cleaning: Duplicates Removal\u003c/h2\u003e\n\u003cp\u003eIn this notebook, we demonstrate how to remove duplicate records using Oracle SQL.\u003c/p\u003e\n\u003cp\u003eWe use the customer insurance lifetime value data set which contains customer financial information, lifetime value, and whether or not the customer bought insurance.\u003c/p\u003e\n\u003cp\u003eThe dataset \u003ccode\u003eCUSTOMER_INSURANCE_LTV_SQL\u003c/code\u003e is generated by the \u003ccode\u003e\"OML Run-me-first\"\u003c/code\u003e notebook, which \u003ccode\u003eMUST\u003c/code\u003e be run before this notebook.\u003c/p\u003e\n\u003chr /\u003e\n\u003ch5\u003e\u003ccode\u003eIMPORTANT\u003c/code\u003e: The \u003ccode\u003e\"OML Run-me-first\"\u003c/code\u003e notebook is available under the menu Templates -\u003e Examples and is a pre-requisite to the current notebook.\u003c/h5\u003e\n\u003chr /\u003e\n\u003cp\u003eCopyright (c) 2023 Oracle Corporation\u003c/p\u003e\n\u003ch6\u003e\u003ca href\u003d\"https: //oss.oracle.com/licenses/upl/\" onclick\u003d\"return ! window.open(\u0027https://oss.oracle.com/licenses/upl/\u0027);\"\u003eThe Universal Permissive License (UPL), Version 1.0\u003c/a\u003e\u003c/h6\u003e\n\u003chr /\u003e\n"
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Expand All @@ -37,15 +37,15 @@
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"status": "FINISHED"
},
{
"title": "Check the number of distinct customer id",
"text": "%sql\n\nSELECT COUNT(DISTINCT CUSTOMER_ID)\nFROM CUSTOMER_INSURANCE_LTV_SQL",
"text": "%sql\n\nSELECT COUNT(DISTINCT CUSTOMER_ID)\nFROM CUSTOMER_INSURANCE_LTV_SQL;\n",
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Expand Down Expand Up @@ -109,15 +109,15 @@
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"dateFinished": "2023-02-17T22:48:34+0000",
"status": "FINISHED"
},
{
"title": "Check the number of total rows in the table. There are duplicated rows",
"text": "%sql\n\nSELECT COUNT(1) FROM CUSTOMER_INSURANCE_LTV_SQL",
"text": "%sql\n\nSELECT COUNT(1) FROM CUSTOMER_INSURANCE_LTV_SQL;\n",
"user": "OMLUSER",
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Expand Down Expand Up @@ -181,17 +181,18 @@
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"dateFinished": "2023-02-17T22:48:34+0000",
"status": "FINISHED"
},
{
"title": "Create a view with all distinct rows",
"text": "%sql\n\nCREATE OR REPLACE VIEW CUSTOMER_INSURANCE_LTV_SQL_UNIQUE AS \nselect *\nfrom CUSTOMER_INSURANCE_LTV_SQL\nwhere rowid in (\n\n select max(rowid) row_id\n from (\n select customer_id, rowid\n from CUSTOMER_INSURANCE_LTV_SQL\n )\n group by customer_id\n ) ",
"text": "%sql\n\nCREATE OR REPLACE VIEW CUSTOMER_INSURANCE_LTV_SQL_UNIQUE AS \nSELECT *\nFROM CUSTOMER_INSURANCE_LTV_SQL\nWHERE rowid IN (\n\n SELECT max(rowid) row_id\n FROM (\n SELECT customer_id, rowid\n FROM CUSTOMER_INSURANCE_LTV_SQL\n )\n GROUP BY customer_id\n ) \n ",
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"progress": 0,
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"language": "sql",
"editOnDblClick": false,
Expand Down Expand Up @@ -248,15 +249,15 @@
"jobName": "paragraph_1643055260594_1721622550",
"id": "20220124-201420_1092363726",
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"dateFinished": "2022-03-10T18:04:54+0000",
"dateStarted": "2023-02-17T22:48:34+0000",
"dateFinished": "2023-02-17T22:48:34+0000",
"status": "FINISHED"
},
{
"title": "Check the number of rows in the table. All rows are distinct",
"text": "%sql\n\nSELECT COUNT(1) FROM CUSTOMER_INSURANCE_LTV_SQL_UNIQUE",
"text": "%sql\n\nSELECT COUNT(1) FROM CUSTOMER_INSURANCE_LTV_SQL_UNIQUE;\n",
"user": "OMLUSER",
"dateUpdated": "2022-03-10T18:04:54+0000",
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"progress": 0,
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Expand Down Expand Up @@ -320,15 +321,15 @@
"jobName": "paragraph_1643055260594_376637058",
"id": "20220124-201420_587942988",
"dateCreated": "2020-11-16T18:18:28+0000",
"dateStarted": "2022-03-10T18:04:54+0000",
"dateFinished": "2022-03-10T18:04:54+0000",
"dateStarted": "2023-02-17T22:48:35+0000",
"dateFinished": "2023-02-17T22:48:35+0000",
"status": "FINISHED"
},
{
"title": "Check the number of distinct CUSTOMER_ID in the table",
"text": "%sql\n\nSELECT COUNT(DISTINCT CUSTOMER_ID) FROM CUSTOMER_INSURANCE_LTV_SQL_UNIQUE",
"text": "%sql\n\nSELECT COUNT(DISTINCT CUSTOMER_ID) FROM CUSTOMER_INSURANCE_LTV_SQL_UNIQUE;\n",
"user": "OMLUSER",
"dateUpdated": "2022-03-10T18:04:54+0000",
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"progress": 0,
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Expand Down Expand Up @@ -392,14 +393,14 @@
"jobName": "paragraph_1643055260594_-313119734",
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"dateCreated": "2020-11-16T18:18:40+0000",
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"dateFinished": "2023-02-17T22:48:35+0000",
"status": "FINISHED"
},
{
"text": "%md\n\n# End of Script\n",
"user": "OMLUSER",
"dateUpdated": "2022-03-10T18:04:55+0000",
"dateUpdated": "2023-02-17T22:48:35+0000",
"progress": 0,
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Expand Down Expand Up @@ -434,14 +435,14 @@
"jobName": "paragraph_1643055260594_-1452388910",
"id": "20220124-201420_1929682519",
"dateCreated": "2020-11-17T00:34:19+0000",
"dateStarted": "2022-03-10T18:04:56+0000",
"dateFinished": "2022-03-10T18:04:56+0000",
"dateStarted": "2023-02-17T22:48:35+0000",
"dateFinished": "2023-02-17T22:48:35+0000",
"status": "FINISHED"
},
{
"text": "%md\n",
"user": "OMLUSER",
"dateUpdated": "2022-03-10T18:04:56+0000",
"dateUpdated": "2023-02-17T22:48:35+0000",
"progress": 0,
"config": {
"editorSetting": {
Expand Down Expand Up @@ -470,8 +471,8 @@
"jobName": "paragraph_1643055260594_1463615022",
"id": "20220124-201420_1402402732",
"dateCreated": "2020-12-15T19:58:03+0000",
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"dateFinished": "2023-02-17T22:48:35+0000",
"status": "FINISHED"
}
],
Expand Down
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