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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Tierney, Brendan, 1970-
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York : McGraw-Hill Education, ©2014.
Temas:
Oracle (Computer file)
Data mining > Computer programs.
Forecasting > Statistical methods.
Exploration de données (Informatique) > Logiciels.
Prévision > Méthodes statistiques.
COMPUTERS > Database Management > Data Mining.
Forecasting > Statistical methods
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Tabla de Contenidos:
  • 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
  • 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
  • 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
  • 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
  • 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

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