Table of Contents
- List of Figures
- List of Tables
- Title and Copyright Information
- Preface
-
New Features and Changes in Oracle Data Miner
-
Oracle Machine Learning Features
- Association Model Aggregation Metrics
-
Enhancements to Algorithm Settings
- Changes to Decision Tree Algorithm Settings
- Changes to Expectation Maximization Algorithm Settings
- Changes to Generalized Linear Models Algorithm Settings
- Changes to k-Means Algorithm Settings
- Changes to Support Vector Machine Algorithm Settings
- Changes to Singular Value Decomposition and Principal Components Analysis Algorithm Settings
- Support for Explicit Semantic Analysis Algorithm
- Enhancement to Oracle Machine Learning Model Detail View
- Enhancements to Filter Column Node
- Mining Model Build Alerts
- R Build Model Node
- Support for Partitioned Models
-
Oracle Machine Learning Features
- Aggregation Node Support for DATE and TIMESTAMP Data Types
- Enhancement to JSON Query Node
- Enhancement to Build Nodes
- Enhancement to Text Settings
- Refresh Input Data Definition
- Support for Additional Data Types
- Support for In-Memory Column
- Support for Workflow Scheduling
- Enhancement to Polling Performance
- Workflow Status Polling Performance Improvement
- Oracle Database Features
-
Oracle Machine Learning Features
- 1 Oracle Data Miner
- 2 Connections for Oracle Machine Learning
- 3 Data Miner Projects
-
4
Workflow
- About Workflows
-
Working with Workflows
- Creating a Workflow
- Deploying Workflows
- Deleting a Workflow
- Loading a Workflow
-
Managing a Workflow
- Exporting a Workflow Using the GUI
- Import Requirements of a Workflow
- Data Table Names
- Workflow Compatibility
- Building and Modifying Workflows
- Missing Tables or Views
- Managing Workflows using Workflow Controls
- Managing Workflows and Nodes in the Properties Pane
- Performing Tasks from Workflow Context Menu
- Oracle Enterprise Manager Jobs
- Renaming a Workflow
- Runtime Requirements
- Running a Workflow
- Scheduling a Workflow
- Workflow Prerequisites
- Workflow Script Requirements
- About Nodes
-
Working with Nodes
- Add Nodes or Create Nodes
- Copy Nodes
- Edit Nodes
- Link Nodes
- Refresh Nodes
- Run Nodes
-
Performing Tasks from the Node Context Menu
- Connect
- Run
- Force Run
- Create Schedule
- Edit
- View Data
- View Models
- Generate Apply Chain
- Refresh Input Data Definition
- Show Event Log
- Deploy
- Show Graph
- Cut
- Copy
- Paste
- Extended Paste
- Select All
- Performance Settings
- Toolbar Actions
- Show Runtime Errors
- Show Validation Errors
- Save SQL
- Validate Parents
- Compare Test Results
- View Test Results
- Go to Properties
- Navigate
- About Parallel Processing
- Setting Parallel Processing for a Node or Workflow
- About Oracle Database In-Memory
-
5
Data Nodes
-
Create Table or View Node
-
Working with the Create Table or View Node
- Creating a Create Table or View Node
- Create Table Node and Compression
- Edit Create Table or View Node
- Select Columns
- View Create Table or View Data
-
Create Table or View Context Menu
- Connect
- Run
- Force Run
- Create Schedule
- Edit
- View Data
- View Models
- Generate Apply Chain
- Refresh Input Data Definition
- Show Event Log
- Deploy
- Show Graph
- Cut
- Copy
- Paste
- Extended Paste
- Select All
- Performance Settings
- Toolbar Actions
- Show Runtime Errors
- Show Validation Errors
- Save SQL
- Validate Parents
- Compare Test Results
- View Test Results
- Go to Properties
- Navigate
- Create the Table or View Node Properties
-
Working with the Create Table or View Node
- Data Source Node
- Explore Data Node
- Graph Node
- SQL Query Node
- Update Table Node
- Target Values Selection
-
Create Table or View Node
- 6 Using the Oracle Data Miner GUI
-
7
Transforms Nodes
- Aggregation
- Data Viewer
- Expression Builder
- Filter Columns Node
- Filter Columns Details
- Filter Rows
- Join
- JSON Query
- Sample
- Transform
-
8
Model Nodes
- Types of Models
- Automatic Data Preparation (ADP)
- Data Used for Model Building
- Model Nodes Properties
- Anomaly Detection Node
- Association Node
- Classification Node
- Clustering Node
- Explicit Feature Extraction Node
- Feature Extraction Node
- Model Node
- Model Details Node
- R Build Node
- Regression Node
- Advanced Settings Overview
- Machine Learning Functions
- 9 Model Operations
-
10
Predictive Query Nodes
- Anomaly Detection Query
- Clustering Query
- Feature Extraction Query
- Prediction Query
- 11 Text Nodes
- 12 Testing and Tuning Models
-
13
Oracle Machine Learning Algorithms
- Anomaly Detection
- Association
- Decision Tree
- Expectation Maximization
- Explicit Semantic Analysis
- Generalized Linear Models
- k-Means
- Naive Bayes
- Nonnegative Matrix Factorization
- Orthogonal Partitioning Clustering
- Singular Value Decomposition and Principal Components Analysis
-
Support Vector Machine
- Support Vector Machine Algorithms
- Building and Testing SVM Models
- Applying SVM Models
- SVM Classification Algorithm Settings
- SVM Classification Test Viewer
- SVM Classification Model Viewer
- SVM Regression Algorithm Settings
- SVM Regression Test Viewer
- SVM Regression Model Viewer
- Settings Information
- Index