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Contents
List of Figures
List of Tables
Title and Copyright Information
Preface
Audience
Documentation Accessibility
Related Documents
Conventions
New Features and Changes in Oracle Data Miner
Oracle Data Mining 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
Explicit Feature Extraction Node
Feature Compare Node
Enhancement to Data Mining Model Detail View
Enhancements to Filter Column Node
Mining Model Build Alerts
R Build Model Node
Support for Partitioned Models
Oracle Data Miner 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
1
Oracle Data Miner
About the Data Mining Process
Overview of Oracle Data Miner
Architecture of Oracle Data Miner
Snippets in Oracle Data Miner
Using Predictive Analytics Snippets
About Oracle Data Miner Repository Installation
Installing the Data Miner Repository Using the GUI
About Dropping the Oracle Data Miner Repository
Dropping the Data Miner Repository Using GUI
About Oracle Data Miner Repository Migration
Migrating the Oracle Data Miner Repository Using the GUI
How to Use Oracle Data Miner
Oracle By Example for Oracle Data Miner 4.1
Sample Data
Oracle Data Miner Online Help
Search the Online Help
Oracle Data Mining Forum
Oracle Data Miner Documentation
2
Connections for Data Mining
About the Data Miner Tab
Prerequisites for Data Mining
Viewing the Data Miner Tab
Creating a Connection
Creating Connections from the Connections Tab
Creating Connections from the Data Miner Tab
Managing a Connection
Viewing and Editing Connection Properties
Removing a Connection
Connecting to a Database
Provide Password
3
Data Miner Projects
Creating a Project
Project Name Restrictions
Managing a Project
Deleting a Project
Expanding a Project
Project Properties
Rename Project
Importing a Workflow
Import Workflow
4
Workflow
About Workflows
Workflow Sequence
Workflow Terminology
Workflow Thumbnail
Components
Workflow Editor
Workflow Properties
Properties
Working with Workflows
Creating a Workflow
Workflow Name Restrictions
Deploying Workflows
Deploy Workflows using Data Query Scripts
Deploy Workflows using Object Generation Scripts
Running Workflow Scripts
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
Network Connection Interruption
Locking and Unlocking Workflows
Scheduling a Workflow
Create Schedule
Repeat
Repeat Hourly
Repeat Daily
Repeat Weekly
Repeat Monthly
Repeat Yearly
Schedule
Save a Schedule
Advanced Settings
Workflow Prerequisites
Workflow Script Requirements
Script File Character Set Requirements
Script Variable Definitions
Scripts Generated
Running Scripts using SQL*Plus or SQL Worksheet
About Nodes
Node Name and Node Comments
Node Types
Node States
Working with Nodes
Add Nodes or Create Nodes
Copy Nodes
Edit Nodes
Editing Nodes through Edit Dialog Box
Editing Nodes through Properties
Link Nodes
Linking Nodes in Components Pane
Node Connection Dialog Box
Change Node Position
Connect Option in Diagram Menu
Deleting a Link
Cancelling a Link
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
Parallel Processing Use Cases
Premise of the Parallel Processing Use Case
Making Transformation Run Faster, using Parallel Processing and Other Methods
Running Graph Node in Parallel
Running a Node in Parallel to Test Performance
Oracle Data Mining Support for Parallel Processing
Setting Parallel Processing for a Node or Workflow
Performance Settings
Edit Node Performance Settings
Edit Node Parallel Settings
About Oracle Database In-Memory
Benefits of Oracle Database In-Memory Column Store
Use Cases of 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
Edit Storage Settings
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
Table
Columns
Automatic Behavior
Data Source Node
Supported Data Types for Data Source Nodes
Support for Date and Time Data
Working with the Data Source Node
Create a Data Source Node
Edit Schema List
Define a Data Source Node
Edit Data Guide
Select Data Guide
JSON Settings
Edit a Data Source Node
Running a Data Source Node
Data Source Node Context Menu
Select Attributes
Data Source Node Viewer
Data
Select Column to Sort By
Graph
Columns
SQL
Data Source Node Properties
Data
Cache
Details
Explore Data Node
Create an Explore Data Node
Edit the Explore Data Node
Input (Explore)
Select Attributes
Statistics (Explore)
Mode (Sampled)
Explore Data Node Viewer
Statistics
Columns
Data
SQL
Export Node Calculations
Perform Tasks from the Explore Data Node Context Menu
Explore Data Node Properties
Input (Properties)
Statistics
Output
Histogram
Sample
Graph Node
Types of Graphs
Box Plot or Box Graph
Supported Data Types for Graph Nodes
Graph Node Context Menu
Running Graph Node
Show Graph
Create a Graph Node
New Graph
Line or Scatter
Bar
Histogram
Box
Settings (Graph Node)
Select Values to Display
Axis Treatment
Graph Node Editor
Zoom Graph
Viewing Data used to Create Graph
Edit Graph
Bar
Box
Histogram
Line or Scatter
Graph Node Properties
Cache (Graph Node)
Details
Data
SQL Query Node
Input for SQL Query Node
SQL Query Restriction
Create a SQL Query Node
SQL Query Node Editor
Oracle R Enterprise Script Support
Oracle R Enterprise Database Roles
SQL Query Node Context Menu
SQL Query Node Properties
Update Table Node
Input and Output for Update Table Node
Data Types for Update Table Node
Create Update Table Node
Update Table Node Automatic Behavior
Edit Update Table Node
Create Table (Update Table)
Select Attributes (Update Table)
Edit Columns (Update Table)
Update Table Node Data Viewer
Update Table Node Context Menu
Update Table Node Properties
Table (Update Table)
Columns (Update Table)
Cache
Details
Target Values Selection
6
Using the Oracle Data Miner GUI
Graphical User Interface Overview
Oracle Data Miner Functionality in the Menu Bar
View Menu
Data Miner
Workflow Jobs
Scheduled Jobs
Structure Window
Structure Window and Workflow
Structure Window and Model Viewers
Structure Window Controls
Tools Menu
Data Miner
Data Miner Preferences
Node Settings
Viewers
Workflow Editor
Workflow Import/Export
Workflow Jobs
Workflow Scheduler
Diagram Menu
Connect
Align
Distribute
Bring to Front
Send to Back
Zoom
Publish Diagram
Oracle Data Miner Online Help
Workflow Jobs
Viewing Workflow Jobs
Working with Workflow Jobs
Workflow Jobs Grid
View an Event Log
Informational Messages
Workflow Jobs Context Menu
Projects
Miscellaneous
Filter
Import Data (Oracle Data Miner)
Filter Out Objects Associated with Oracle Data Mining
Copy Charts, Graphs, Grids, and Rules
7
Transforms Nodes
Aggregation
Creating Aggregate Nodes
Editing Aggregate Nodes
Edit Group By
Define Aggregation
Edit Aggregate Element
Add Column Aggregation
Add Custom Aggregation
Aggregate Node Properties
Cache
Details
Aggregate Node Context Menu
Data Viewer
Data
Select Column to Sort By
Graph
Columns
SQL
Expression Builder
Functions
Filter Columns Node
Creating Filter Columns Node
Editing Filter Columns Node
Exclude Columns
Define Filter Columns Settings
Explore Dependencies
Predictor Dependencies
Performing Tasks After Running Filter Columns Node
Columns Filter Details Report
Attribute Importance
Attribute Importance Viewer
Filter Columns Node Properties
Filter Columns Node Context Menu
Filter Columns Details
Creating the Filter Columns Details Node
Editing the Filter Columns Details Node
Filter Columns Details Node Properties
Filter Columns Details Node Context Menu
Filter Rows
Creating a Filter Rows Node
Edit Filter Rows
Filter
Columns
Filter Rows Node Properties
Filter Rows Node Context Menu
Join
Create a Join Node
Edit a Join Node
Edit Join Node
Edit Columns
Edit Output Data Column
Resolve
Join Node Properties
Join Node Context Menu
JSON Query
Create JSON Query Node
JSON Query Node Editor
JSON
Structure
Data
Filter Settings
Additional Output
Edit Output Data Column Dialog
Aggregate
Add Aggregations
Edit Sub Group By
Edit Group By
Preview
Output Columns
Output Data
JSON Query Node Properties
Output
Cache
Details
JSON Query Node Context Menu
Data Types and their Supported Operators
Sample
Sample Nested Data
Creating a Sample Node
Edit Sample Node
Random
Top N
Stratified
Custom Balance
Sample Node Properties
Cache
Details
Sample Node Context Menu
Transform
Supported Transformations
Binning
Recode
Custom
Missing Values
Normalization
Outlier
Support for Date and Time Data Types
Creating Transform Node
Edit Transform Node
Add Transform
Binning
Bin Equal Width (Number)
Bin Quantile
Bin Top N
Custom
Missing Values
Normalization
Outlier
Use Existing Column
Add or Edit Multiple Transforms
Add Custom Transform
Apply Transform Wizard
Define Columns
Edit Transform
Edit Custom Transform
Transform Node Properties
Transform Node Context Menu
8
Model Nodes
Types of Models
Automatic Data Preparation (ADP)
Numerical Data Preparation
Manual Data Preparation
Data Used for Model Building
Viewing and Changing Data Usage
Input Tab of Build Editor
Automatic Input
Manual Input
Advanced Settings
Text
Model Nodes Properties
Models
Output Column
Add Model
Build
Test
Details
Anomaly Detection Node
Create Anomaly Detection Node
Edit Anomaly Detection Node
Build (AD)
Partition
Input
Sampling
Text
Data for Model Build
Advanced Model Settings
Add Model (AD)
Data Usage
Anomaly Detection Node Properties
Models (AD)
Output Column (AD)
Add Model (AD)
Build (AD)
Partition
Details
Anomaly Detection Node Context Menu
Association Node
Behavior of the Association Node
Create Association Node
Edit Association Build Node
Build
Select Columns (AR)
Partition
Advanced Settings
Filter
Find Items
Aggregates
Sampling
Advanced Settings for Association Node
Association Node Context Menu
Association Build Properties
Models (AR)
Add Model (AR)
Output Column (AR)
Build (AR)
Partition
Filter
Aggregates
Sampling
Details
Classification Node
Default Behavior for Classification Node
Create a Classification Node
Data for Model Build
Edit Classification Build Node
Build (Classification)
No Case ID
Partition
Add Partition Column
Sampling
Input
Text
Advanced Settings for Classification Models
Add Models
Add Model (Classification)
Classification Node Properties
Classification Node Models
Classification Node Output Column
Classification Node Build
Classification Node Test
Target Values Selection
Partition
Details
Classification Build Node Context Menu
View Test Results
Compare Test Results
Clustering Node
Default Behavior for Clustering Node
Create Clustering Build Node
Data for Model Build
Edit Clustering Build Node
Build (Clustering)
Add Model (Clustering)
Partition
Sampling
Input
Text
Advanced Settings for Clustering Models
Clustering Build Node Properties
Models
Add Model (Clustering)
View Models
Clustering Node Output Column
Build
Partition
Sampling
Details
Clustering Build Node Context Menu
Explicit Feature Extraction Node
Create Explicit Feature Extraction Node
Edit Explicit Feature Extraction Node
Build
Add Model
Partition
Add Partitioning Columns
Sampling
Input
Text
Advanced Model Settings
Explicit Feature Extraction Build Properties
Models
Build
Partition
Details
Explicit Feature Extraction Context Menu
Feature Extraction Node
Default Behavior of Feature Extraction Node
Create Feature Extraction Node
Data for Model Build
Edit Feature Extraction Build Node
Build (Feature Extraction)
Add Model (Feature Extraction)
Partition
Sampling
Input
Text
Stoplist Details
Add Stopwords Stopthemes from Features
Advanced Settings for Feature Extraction
Feature Extraction Node Properties
Feature Extraction Node Context Menu
Model Node
Create a Model Node
Edit Model Selection
Model Constraints
Model Node Properties
Models (Model Node)
Details
Model Node Context Menu
Model Details Node
Model Details Node Input and Output
Create Model Details Node
Edit Model Details Node
Edit Model Selection Details
Model Details Automatic Specification
Default Model and Output Type Selection
Model Details Node Properties
Models (Model Details)
Output (Model Details)
Cache (Model Details)
Details
Model Details Node Context Menu
View Data (Model Details)
Model Details Per Model
R Build Node
Create R Build Node
Edit R Build Node
Build
Add Model (R Build Node)
Partition
Add Partitioning Columns
Input
Sampling
Text
Advanced Settings (R Build Node)
R Build Node Properties
R Build Node Context Menu
Regression Node
Default Behavior for Regression Node
Create a Regression Node
Data for Model Build
Edit Regression Build Node
Build
Add Model (Regression)
Partition
Sampling
Input
Text
Advanced Settings for Regression Models
Regression Node Properties
Models (Regression)
Output Column
Build (Regression)
Partition
Details
Test (Regression)
Regression Node Context Menu
Advanced Settings Overview
Upper Pane of Advanced Settings
Lower Pane of Advanced Settings
Data Usage
Algorithm Settings
Performance Settings
Mining Functions
Classification
Building Classification Models
Comparing Classification Models
Applying Classification Models
Classification Algorithms
Regression
Building Regression Models
Applying Regression Models
Regression Algorithms
Anomaly Detection
Building Anomaly Detection Models
Applying Anomaly Detection Models
Clustering
Using Clusters
Calculating Clusters
Algorithms for Clustering
Association
Transactions
Feature Extraction and Selection
Feature Selection
Feature Extraction
9
Model Operations
Apply Node
Apply Preferences
Apply Node Input
Apply Node Output
Creating an Apply Node
Apply and Output Specifications
Edit Apply Node
Predictions
Add or Edit Apply Output Column
Add Output Apply Column Dialog
Define Apply Columns Wizard
Models
Output Specifications
Define Top N
Additional Output
Evaluate and Apply Data
Edit Apply Node
Predictions
Additional Output
Apply Columns
Apply Node Properties
Apply Node Context Menu
Connect
Run
Force Run
Create Schedule
Edit
View Data
Generate Apply Chain
Show Event Log
Show Validation Errors
Validate Parents
Deploy
Save SQL
Cut
Copy
Paste
Select All
Performance Settings
Go to Properties
Navigate
Apply Data Viewer
Feature Compare Node
Create Feature Compare Node
Feature Compare
Feature Compare Node Context Menu
Connect
Run
Force Run
Create Schedule
Edit
View Data
Generate Apply Chain
Show Event Log
Show Validation Errors
Validate Parents
Deploy
Save SQL
Cut
Copy
Paste
Select All
Performance Settings
Go to Properties
Navigate
Test Node
Support for Testing Classification and Regression Models
Test Node Input
Automatic Settings
Creating a Test Node
Edit Test Node
Select Model
Compare Test Results Viewer
Test Node Properties
Models
Selected Models
Test
Details
Test Node Context Menu
10
Predictive Query Nodes
Anomaly Detection Query
Create an Anomaly Detection Query Node
Edit an Anomaly Detection Query
Edit Anomaly Prediction Output
Add Anomaly Function
Edit Anomaly Function Dialog
Anomaly Detection Query Properties
Anomaly Detection Query Context Menu
Connect
Run
Force Run
Create Schedule
Edit
View Data
Generate Apply Chain
Show Event Log
Deploy
Cut
Copy
Paste
Extended Paste
Select All
Performance Settings
Toolbar Actions
Show Runtime Errors
Show Validation Errors
Save SQL
Validate Parents
Go to Properties
Clustering Query
Create a Clustering Query
Edit a Clustering Query
Edit Cluster Prediction Outputs
Add Cluster Function
Edit Cluster Function
Clustering Query Properties
Clustering Query Context Menu
Connect
Run
Force Run
Create Schedule
Edit
View Data
Generate Apply Chain
Show Event Log
Deploy
Cut
Copy
Paste
Extended Paste
Select All
Performance Settings
Toolbar Actions
Show Runtime Errors
Show Validation Errors
Save SQL
Validate Parents
Go to Properties
Feature Extraction Query
Create a Feature Extraction Query
Edit Feature Extraction Query
Edit Feature Prediction Outputs
Add Feature Function
Edit Feature Function
Feature Extraction Query Properties
Feature Extraction Query Context Menu
Connect
Run
Force Run
Create Schedule
Edit
View Data
Generate Apply Chain
Show Event Log
Deploy
Cut
Copy
Paste
Extended Paste
Select All
Performance Settings
Toolbar Actions
Show Runtime Errors
Show Validation Errors
Save SQL
Validate Parents
Go to Properties
Prediction Query
Create a Prediction Query
Edit a Prediction Query
Add Target
Add Partitioning Columns
Add Partitioning Expressions
Edit Prediction Output
Add Prediction Output Function
Edit Prediction Function Dialog
Modify Input
View Heuristic Results Details
Add Additional Output
Add Supplemental Dialog
Run Predictive Query Node
View Data for a Predictive Query
View Prediction Details
Prediction Query Properties
Prediction Query Node Context Menu
Connect
Run
Force Run
Create Schedule
Edit
View Data
Generate Apply Chain
Show Event Log
Deploy
Cut
Copy
Paste
Extended Paste
Select All
Performance Settings
Toolbar Actions
Show Runtime Errors
Show Validation Errors
Save SQL
Validate Parents
Go to Properties
11
Text Nodes
Oracle Text Concepts
Text Mining in Oracle Data Mining
Data Preparation for Text
Text Processing in Oracle Data Mining 12
c
Release 1 (12.1) and Later
Text Processing in Oracle Data Mining 11
g
Release 2 (11.2) and Earlier
Apply Text Node
Default Behavior for the Apply Text Node
Create an Apply Text Node
Edit Apply Text Node
View the Text Transform (Apply)
Apply Text Node Properties
Transforms
Cache
Sample
Details
Apply Text Node Context Menu
Build Text
Default Behavior of the Build Text Node
Create Build Text Node
Edit Build Text Node
View the Text Transform
Add/Edit Text Transform
Stoplist Editor
New Stoplist Editor
Add Stopwords/Stopthemes
Build Text Node Properties
Transforms
Sample
Cache
Details
Build Text Node Context Menu
Text Reference
Create a Text Reference Node
Edit Text Reference Node
Select Build Text Node
Text Reference Node Properties
Transforms
Details
Text Reference Node Context Menu
12
Testing and Tuning Models
Testing Classification Models
Test Metrics for Classification Models
Performance
Predictive Confidence
Average Accuracy
Overall Accuracy
Cost
Performance Matrix
Receiver Operating Characteristics (ROC)
How to Use ROC
Lift
Profit and ROI
Profit and ROI Example
Profit and ROI Use Case
Compare Classification Test Results
Compare Test Results
Edit Test Selection (Classification and Regression)
Classification Model Test Viewer
Performance
Performance Matrix
Show Detail
Compare Models
ROC
Edit Test Result Selection
ROC Detail Dialog
Lift
Lift Detail
Profit
Profit Detail Dialog
Profit Setting Dialog
Model Partitions
Select Partition
Viewing Test Results
Tuning Classification Models
Remove Tuning
Cost
Costs and Benefits
Costs
Benefits
Benefit
ROC
ROC Tuning Steps
Select Custom Operating Point
Receiver Operating Characteristics
Lift
About Lift
Profit
Profit Setting
Profit
Testing Regression Models
Residual Plot
Regression Statistics
Compare Regression Test Results
Compare Test Results
Regression Model Test Viewer
Performance (Regression)
Residual
13
Data Mining Algorithms
Anomaly Detection
Applying Anomaly Detection Models
Algorithm Settings for AD
Anomaly Detection Algorithm Settings for Linear or System Determined Kernel
Active Learning
Complexity Factor
Rate of Outliers
Tolerance Value
Anomaly Detection Algorithm Settings for Gaussian Kernel
Active Learning
Cache Size (Gaussian Kernel)
Complexity Factor
Rate of Outliers
Standard Deviation (Gaussian Kernel)
Tolerance Value
Anomaly Detection Model Viewer
AD Model Viewer for Gaussian Kernel
Settings (AD)
Input (AD)
Anomaly Detection Algorithm Settings
AD Model Viewer for Linear Kernel
Coefficients (SVMC Linear)
Settings (AD)
Compare (SVMC Linear)
Viewing Models in Model Viewer
Association
Calculating Associations
Itemsets
Association Rules
Data for AR Models
Support for Text (AR)
Troubleshooting AR Models
Algorithm Settings for Association Rules
AR Model Viewer
AR Rules
AR Rules Grid
AR Rules Display
Rule Details
Sorting
Filtering
Item Filters
Add Item Filter
Itemsets
Itemsets Display
Itemset Details
Settings (AR)
Summary
Viewing Models in Model Viewer
Decision Tree
Decision Tree Algorithm
Decision Tree Rules
Build, Test, and Apply Decision Tree Models
Decision Tree Algorithm Settings
Decision Tree Model Viewer
Save Rules
Settings (DT)
DT Summary
DT Inputs
Partition Keys
DT Target Values
Expectation Maximization
Build and Apply an EM Model
EM Algorithm Settings
EM Data Preparation and Analysis Settings
EM Model Viewer
EM, KM, and OC Tree Viewer
Cluster (Viewer)
Cluster Model Settings (Viewer)
EM, KM, and OC Compare
EM Component
EM Details
Explicit Semantic Analysis
Uses of Algorithm
Supported Mining Models
ESA Algorithm Settings
ESA Model Viewer
Features
Settings (ESA)
Coefficients ESA
Generalized Linear Models
Generalized Linear Models Overview
Linear Regression
Logistic Regression
Data Preparation for GLM
GLM Classification Models
GLM Classification Algorithm Settings
Feature Selection Option Dialog
Choose Reference Value (GLMC)
Ridge Regression Option Dialog (GLMC)
GLM Classification Model Viewer
GLMC Details
GLMC Coefficients
Sort and Search GLMC Coefficients
GLMC Compare
GLMC Diagnostics
GLMC Settings
Summary
Inputs
Partition Keys
Weights
GLMC Target Values
GLM Regression Models
GLM Regression Algorithm Settings
Ridge Regression Option Dialog (GLMR)
Choose Reference Value (GLMR)
GLM Regression Model Viewer
GLMR Coefficients
GLMR Details
GLMR Diagnostics
GLMR Settings
GLMR Summary
GLMR Inputs
GLMR Coefficients
GLMR Details
GLMR Diagnostics
k-
Means
k-
Means Algorithm
KM Algorithm Settings
KM Model Viewer
EM, KM, and OC Tree Viewer
Cluster (Viewer)
EM, KM, and OC Compare
Compare Cluster with Population
Missing Histograms in a Cluster
Rename Cluster
KM Settings
Cluster Model Settings (Viewer)
Naive Bayes
Naive Bayes Algorithm
Advantages of Naive Bayes
Naive Bayes Test Viewer
Naive Bayes Model Viewer
Probabilities (NB)
Grid
Fetch Size
Grid Filter
Compare (NB)
Settings (NB)
Settings (NB)
Summary (NB)
Input (NB)
Partition Keys
Weights
Target Values
Nonnegative Matrix Factorization
Using Nonnegative Matrix Factorization
How Does Nonnegative Matrix Factorization Work
NMF Algorithm Settings
NMF Model Viewer
Coefficients (NMF)
Rename (NMF)
Filter (NMF)
Features
Settings (NMF)
Summary (NMF)
Inputs (NMF)
Orthogonal Partitioning Clustering
O-Cluster Algorithm
OC Algorithm Settings
OC Model Viewer
EM, KM, and OC Tree Viewer
Cluster (Viewer)
EM, KM, and OC Compare
Detail (OC)
Settings (OC)
Summary (OC)
Inputs (OC)
Interpreting Cluster Rules
Singular Value Decomposition and Principal Components Analysis
Build and Apply SVD and PCA Models
PCA Algorithm Settings
Solver (Stochastic QR Computation)
PCA Model Viewer
Coefficients (PCA)
Rename (PCA)
Filter (PCA)
PCA Scree Plot
Features
PCA Details
Settings (PCA)
Summary (PCA)
Inputs (PCA)
SVD Algorithm Settings
SVD Model Viewer
Coefficients (SVD)
Rename (SVD)
Filter (SVD)
Features
SVD Singular Values
SVD Details
Settings (SVD)
Summary (SVD)
Inputs (SVD)
Support Vector Machine
Support Vector Machine Algorithms
How Support Vector Machines Work
SVM Kernel Functions
Building and Testing SVM Models
SVM Classification Models
SVM Weights
SVM Regression Models
SVM Anomaly Detection Models
Applying SVM Models
Applying One-Class SVM Models
SVM Classification Algorithm Settings
Algorithm Settings for Linear or System Determined Kernel (SVMC)
Solver (Sub-Gradient Descend)
Algorithm Settings for Gaussian Kernel (SVMC)
Active Learning
Complexity Factor
Tolerance Value
Cache Size (Gaussian Kernel)
Standard Deviation (Gaussian Kernel)
SVM Classification Test Viewer
SVM Classification Model Viewer
SVMC Model Viewer for Models with Linear Kernel
Coefficients (SVMC Linear)
Compare (SVMC Linear)
Settings (SVMC)
SVMC Model Viewer for Models with Gaussian Kernel
Summary (SVMC)
Inputs (SVMC)
Weights (SVMC)
Target Values (SVMC)
Coefficients (SVMC Linear)
Coefficients Grid (SVMC)
Compare (SVMC Linear)
Search
Propensity
Settings (SVMC)
Summary (SVMC)
Inputs (SVMC)
Partition Keys
Weights (SVMC)
Algorithm Settings for SVMC
SVM Regression Algorithm Settings
Algorithm Settings for Linear or System Determined Kernel (SVMR)
Tolerance Value
Active Learning
Complexity Factor
Algorithm Settings for Gaussian Kernel (SVMR)
Tolerance Value
Complexity Factor
Active Learning
Standard Deviation (Gaussian Kernel)
Cache Size (Gaussian Kernel)
Automatic Data Preparation
SVM Regression Test Viewer
SVM Regression Model Viewer
SVMR Model Viewer for Models with Linear Kernel
Coefficients (SVMR)
Settings (SVMR)
SVMR Model Viewer for Models with Gaussian Kernel
Summary (SVMR)
Inputs (SVMR)
Settings Information
General Settings
Automatic Data Preparation
Other Settings
Epsilon Value
Index
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