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Predictive analytics using Oracle Data Miner : develop & use data mining models in Oracle Data Miner, SQL & PL/SQL /
"The only Oracle Press guide to developing next-generation predictive analytics applications with Oracle Data MinerPredictive analytics is the most technically sophisticated approach to staying ahead of competitors using advanced techniques to find patterns in enterprise data. This is an essent...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York :
McGraw-Hill Education,
©2014.
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Tierney, Brendan, |d 1970- | |
| 245 | 1 | 0 | |a Predictive analytics using Oracle Data Miner : |b develop & use data mining models in Oracle Data Miner, SQL & PL/SQL / |c Brendan Tierney. |
| 260 | |a New York : |b McGraw-Hill Education, |c ©2014. | ||
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| 500 | |a Includes index. | ||
| 520 | |a "The only Oracle Press guide to developing next-generation predictive analytics applications with Oracle Data MinerPredictive analytics is the most technically sophisticated approach to staying ahead of competitors using advanced techniques to find patterns in enterprise data. This is an essential how-to guide for data scientists, data miners, data analysts, Oracle developers, and DBAs. Written by an Oracle ACE Director, Predictive Analytics Using Oracle Data Miner shows you how to use this powerful tool to build and apply advanced data mining models and perform data mining tasks in SQL and PL/SQL. Guidance on how to migrate the data mining models from a test environment to a production environment is included. Best practices for creating predictive models that help target key customers, develop detailed customer profiles, find and prevent fraud, stay ahead of the competition, and realize greater profits Reveals how to unlock the power of native SQL functions within the Oracle Database "-- |c Provided by publisher | ||
| 520 | |a "Perform in-database data mining to unlock hidden insights in data. Written by an Oracle ACE Director, Predictive Analytics Using Oracle Data Miner shows you how to use this powerful tool to create and deploy advanced data mining models. Covering topics for the data scientist, Oracle developer, and Oracle database administrator, this Oracle Press guide shows you how to get started with Oracle Data Miner and build Oracle Data Miner models using SQL and PL/SQL packages. You'll get best practices for integrating your Oracle Data Miner models into applications to automate the discovery and distribution of business intelligence predictions throughout the enterprise"-- |c Provided by publisher | ||
| 505 | 0 | |a Cover -- About the Author -- About the Technical Editor -- Title Page -- Copyright Page -- Contents at a Glance -- Contents -- Acknowledgments -- Introduction -- PART I: Oracle Data Miner Fundamentals -- Chapter 1: Oracle Data Miner -- In-Database Data Mining with Oracle Data Mining -- Oracle Advanced Analytics Option -- Oracle Data Mining -- Oracle R Enterprise (ORE) -- History of Data Mining in Oracle -- Oracle Data Mining Components -- Oracle Data Mining Architecture -- Oracle Data Miner GUI Tool -- Oracle Data Mining Using SQL and PL/SQL -- Oracle Statistical Functions | |
| 505 | 8 | |a Applications Powered by Oracle Data Mining -- How Are Customers Using Oracle Advanced Analytics -- Customer Success Stories -- Chapter 2: The Predictive Modeling Lifecycle -- Predictive Modeling Lifecycles -- Knowledge Discovery in Data (KDD) Process -- SEMMA -- CRISP-DM -- Business Understanding -- Data Understanding -- Data Preparation -- Modeling -- Evaluation -- Deployment -- Summary -- Chapter 3: How to Install, Set Up, and Get Started -- Enabling the Oracle Advanced Analytics Option -- Creating a Data Mining Tablespace -- Creating an ODM Schema | |
| 505 | 8 | |a Creating a Connection for Your DM User in SQL Developer -- Creating the Oracle Data Mining Repository -- Using SQL Developer to Create the ODM Repository -- Using SQL Scripts to Create the ODM Repository -- Setting Up Additional Users to Access ODM -- ODM Schema System Privileges -- Setting Up and Using the Pre-built Database Appliance -- Summary -- PART II: Using the Oracle Data Miner Tool -- Chapter 4: ODM Menus, Projects, and Workflows -- The ODM Menus -- Creating a Project -- Creating, Exporting, and Importing a Workflow -- Creating a Workflow -- Exporting a Workflow -- Importing a Workflow | |
| 505 | 8 | |a Adjusting the Layout -- The ODM Workflow Menu -- The Components Workflow Editor -- Summary -- Chapter 5: Exploring Your Data -- Gathering Statistics and Exploring Your Data -- Adding a Data Source -- Data Source Properties -- The Explore Data Node -- Building Up a Story About the Data -- Exploring the Data Based on Attribute Grouping -- Graphs -- Creating a Graph -- SQL Query Node -- Feature Selection -- Summary -- Chapter 6: Data Preparation -- Aggregate -- Using the Aggregation Wizard -- Adding a New Aggregation-Level Attribute -- Adding an Aggregation Expression -- Filter Columns | |
| 505 | 8 | |a Filter Columns Details -- Filter Rows -- Join -- Sample -- Transform -- Automatic Data Preparation (ADP) -- Summary -- Chapter 7: Association Rule Analysis -- What Is Association Rule Analysis? -- Association Rule Analysis in Oracle -- Building Association Rules Using ODM -- Defining the Data Source -- Creating the Association Node -- Model Settings -- Association Node Properties Tab -- Viewing the Association Rules -- Generated Rules -- Generated Itemsets -- Adding a Data Source Node for Transaction Descriptions -- Applying Filters to the Association Rules | |
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
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| 650 | 0 | |a Forecasting |x Statistical methods. | |
| 650 | 6 | |a Exploration de données (Informatique) |x Logiciels. | |
| 650 | 6 | |a Prévision |x Méthodes statistiques. | |
| 650 | 7 | |a COMPUTERS |x Database Management |x Data Mining. |2 bisacsh | |
| 650 | 7 | |a Forecasting |x Statistical methods |2 fast | |
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