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At a Glance; Contents; About the Author; About the Technical Reviewer; Acknowledgments; Introduction; Chapter 1: Getting Started With Oracle Advanced Analytics; Data Science; Business Understanding; Data Understanding; Data Preparation; Modeling; Evaluation; Deployment; Machine Learning; Supervised Learning; Unsupervised Learning; Getting Started with Oracle Advanced Analytics; Oracle Data Miner; DBMS_DATA_MINING_TRANSFORMATION for data preprocessing; DBMS_DATA_MINING for creating, testing, and applying models; DBMS_PREDICTIVE_ANALYTICS to create models on the fly.
R Technologies in OracleOracle R Enterprise; Advantages of using Oracle R Enterprise; Analytical SQL and PLSQL Functions; Package DBMS_STATS_FUNC; SQL Functions; Bucketing functions; Windowing functions; LAG and LEAD functions; PIVOT and UNPIVOT functions; Summary; Chapter 2: Installation and Hello World; Booting Up Oracle Data Miner; Installation Prerequisites; Installation; Welcome to the World-Oracle Data Miner; SQL Developer Components for ODM; ODM Data Dictionary; Boot Up Oracle R Enterprise; Prerequisites; Oracle R Distribution; Oracle R Enterprise Server Installation.
Oracle R Enterprise Client InstallationInstall Supporting Packages for the ORE Client; Welcome to the World of Oracle R Enterprise; ORE Data Dictionary; Summary; Chapter 3: Clustering Methods; Clustering Approaches; The k-means Algorithm; k-means in Oracle Advanced Analytics; Clustering Rules Evaluation Metrics; Parameters to Tune k-means Clustering; Creating a Cluster Model in Oracle Advanced Analytics; Clustering using SQL and PLSQL; Clustering using Oracle R Enterprise; Creating a cluster model using SQL Developer; Case Study-Customer Segmentation; Business understanding.
Data understandingRFM Segmentation-Data Preparation; RFM Segmentation-DATA Modeling ; Need-Based Segmentation-Data Preparation; Need-Based Segmentation-Data Modeling ; Result Evaluation; Understanding the clusters; Deployment-Storing the Results Back to the Database; Assigning Segments to New Customers; Summary; Chapter 4: Association Rules; Introduction to Association Rules; Terminologies Associated with Association Rules; Working of an Apriori Algorithm; Identify Interesting Rules; Algorithm Settings; Model Settings; Association Rules Using SQL and PLSQL.
Creating the Association Rules Model Using Oracle R EnterpriseCreating the Association Model Using SQL Developer; Case Study-Market Basket Analysis; Business Understanding; Data Understanding; Data Preparation; Data Modeling; High-Level Technical Overview; Execution; Summary; Chapter 5: Regression Analysis; Understanding Relationships; Regression Analysis; Working of OLS Regression; Assumptions of OLS; OLS Regression in Oracle Advanced Analytics; GLM Regression; Ridge Regression; Parameters to Tune the GLM Model; GLM and Ridge Regression in Oracle Advanced Analytics.
R Technologies in OracleOracle R Enterprise; Advantages of using Oracle R Enterprise; Analytical SQL and PLSQL Functions; Package DBMS_STATS_FUNC; SQL Functions; Bucketing functions; Windowing functions; LAG and LEAD functions; PIVOT and UNPIVOT functions; Summary; Chapter 2: Installation and Hello World; Booting Up Oracle Data Miner; Installation Prerequisites; Installation; Welcome to the World-Oracle Data Miner; SQL Developer Components for ODM; ODM Data Dictionary; Boot Up Oracle R Enterprise; Prerequisites; Oracle R Distribution; Oracle R Enterprise Server Installation.
Oracle R Enterprise Client InstallationInstall Supporting Packages for the ORE Client; Welcome to the World of Oracle R Enterprise; ORE Data Dictionary; Summary; Chapter 3: Clustering Methods; Clustering Approaches; The k-means Algorithm; k-means in Oracle Advanced Analytics; Clustering Rules Evaluation Metrics; Parameters to Tune k-means Clustering; Creating a Cluster Model in Oracle Advanced Analytics; Clustering using SQL and PLSQL; Clustering using Oracle R Enterprise; Creating a cluster model using SQL Developer; Case Study-Customer Segmentation; Business understanding.
Data understandingRFM Segmentation-Data Preparation; RFM Segmentation-DATA Modeling ; Need-Based Segmentation-Data Preparation; Need-Based Segmentation-Data Modeling ; Result Evaluation; Understanding the clusters; Deployment-Storing the Results Back to the Database; Assigning Segments to New Customers; Summary; Chapter 4: Association Rules; Introduction to Association Rules; Terminologies Associated with Association Rules; Working of an Apriori Algorithm; Identify Interesting Rules; Algorithm Settings; Model Settings; Association Rules Using SQL and PLSQL.
Creating the Association Rules Model Using Oracle R EnterpriseCreating the Association Model Using SQL Developer; Case Study-Market Basket Analysis; Business Understanding; Data Understanding; Data Preparation; Data Modeling; High-Level Technical Overview; Execution; Summary; Chapter 5: Regression Analysis; Understanding Relationships; Regression Analysis; Working of OLS Regression; Assumptions of OLS; OLS Regression in Oracle Advanced Analytics; GLM Regression; Ridge Regression; Parameters to Tune the GLM Model; GLM and Ridge Regression in Oracle Advanced Analytics.