# Oracle Data Miner 10.2.0.4.1

July 2008

## Table of Contents

Oracle Data Miner 10.2.0.4.1 is a patch release for Oracle Data Miner 10.2.0.4.

Oracle Data Miner replaces all previous user interfaces to Oracle Data Mining, including Oracle Data Miner 10.1 and Data Mining for Java (DM4J). Models built using Oracle Data Miner 10.1 and DM4J cannot be used with Oracle Data Mining 10.2 and 11.1.

Note: You cannot connect to an Oracle 11g database using Oracle Data Miner 10.2; to connect to an Oracle 11g database, use Oracle Data Miner 11.1.

This document provides a brief overview of new features of Oracle Data Mining 10.2 and Oracle Data Miner 10.2.0.4, along with installation instructions for Oracle Data Miner.

These release notes describe how to install Oracle Data Miner on Mac OS.

## Compatibility with Previous Releases of Oracle Data Miner

Models built using Oracle Data Miner 10.1 cannot be used with Oracle Data Miner 10.2.

Oracle Data Miner requires Oracle 10g Release 2; you cannot connect to any other version of Oracle Database. Any patch version of Oracle 10g Release 2 is compatible with Oracle Data Miner.

Oracle Data Miner 10.1 preferences and connection information will be migrated automatically when you first launch Data Miner 10.2. You may have to reenter passwords.

You can have multiple versions (for example, 10.2 and 11.1) of Oracle Data Miner installed on the same system; they must be unzipped into different directories. Each version of Oracle Data Miner must connect to the correct version of Oracle Database.

## Support and Feedback

If you encounter problems when using Oracle Data Miner, you can report them to Oracle Support (requires current product support contract) at Oracle MetaLink.

You can post general comments and suggestions to the Data Mining Discussion Forum on Oracle Technology Network.

## Oracle Data Miner 10.2 Overview

Oracle Data Miner supports the new Oracle Data Mining 10.2 features, as described in What’s New in Oracle Data Mining?.

Oracle Data Mining includes native import/export facilities for moving data mining objects to other schemas. This is often a required step during deployment. Model import/export is not supported by Oracle Data Miner; it is supported by the Oracle Data Mining Java and PL/SQL programmatic interfaces. For information, see Oracle Data Mining Administrator’s Guide.

The rest of this section briefly describes the following new features of Oracle Data Miner 10.2:

- Mining activity redesign, with improved heuristics
- Support for data specified as joins to a case table
- Support for mixed case names
- Receiver Operating Characteristics (ROC) for classification model evaluation
- Predictive Quality for classification model evaluation
- Improved Classification Accuracy Viewer
- Residuals Plots for regression model evaluation
- Publish data mining results as Oracle Database Tables
- Predict and Explain automated data mining
- Oracle Data Miner PL/SQL Code Generator
- Model wizards removed

### Mining Activity Redesign

A Mining Activity is a step-by-step guide for model build, apply, or test. A Build Activity outlines steps for data preparation, model build, and model test, where appropriate; the exact steps depend on the algorithm selected. An Apply Activity guides users through data preparation and model apply for a model created using a Build Activity or a model created outside of Data Miner using either the Oracle Data Mining 10.2 Java or PL/SQL API. A Test Activity guides users through data preparation and model test for a model created using a Build Activity or a model created outside of Data Miner using either the Oracle Data Mining 10.2 Java or PL/SQL API.

Mining Activities store metadata about model creation to simplify processing. For example, data that a model is applied to must be prepared in the same way as the data used to build the model. An Apply Activity uses the metadata from the Build Activity to prepare the data correctly for the apply operation.

The Mining Activities for Oracle Data Miner 10.2 have improved heuristics, especially for the data preparation steps.

Mining Activities are now available from the Activity menu. You can select a Build activity, an Apply activity, or a Test activity.

Mining Activities support the new functionality of Oracle Data Mining 10.2. For example, there are anomaly detection activities and classification activities that use the Decision Tree algorithm.

Once an activity is created, you can run an activity in several ways:

- Run the activity as soon as the activity definition is complete.
- Run the activity step by step.
- Complete the activity by clicking Start; this option runs all remaining steps of the activity.

### Support for Data Specified as Joins to a Case Table

You can specify data as joins to a case table for input to a mining activity. The joins can be one-to-one or one-to-many. One-to-many joins support transactional data.

### Support for Mixed Case Names

Names of tables and views, columns in tables and views, schemas, and mining objects except for model names and test metrics names may have mixed case. If you want a name to have both uppercase and lowercase letters in it, enclose the name in double quotation marks (`"`).

Model names and test metric names, however, are restricted to 25 or fewer characters and must be uppercase letters.

### Improved Transformation Wizards

Oracle Data Miner has revised versions of the Sample and Stratified Sample transformation wizards that are easier to use.

### New Model and Results Viewers

Model and results viewers were redesigned, and new viewers were created for new models and results. The new model viewers are the Decision Tree Viewer, the Residual Plot Viewer, and the Anomaly Detection Viewer. The new results viewers are viewers for Predict and Explain, the new ROC viewer, and combined test metric viewers. The new Association Rules viewer incorporates lookup on item code. Model viewers now support automatic model transparency. A model is built on transformed data such as normalized or binned data; the results are converted based on transformations so that they reflect values in the original input data.

### Model Evaluation

Oracle Data Miner supports Receiver Operator Characteristics (ROC) for classification models. Oracle Data Miner also supports Test activities.

Receiver Operating Characteristics (ROC) analysis is a useful method for evaluating classification models. ROC curves can be used to compare individual models and to determine thresholds which yield a high proportion of positive hits.

Residuals plots for regression models allow you to identify regions where the predictions are more accurate and less accurate.

For classification and regression models, Oracle Data Miner calculates the Predictive Confidence of the model, which measures how much better the model is than a naive model.

### Publish as Database Table

Tools | Publish as Database Table publishes data mining results as Database tables or views. You can publish the following results:

- Attribute Importance
- Association Rules
- Apply Results
- Decision Tree Rules
- Clustering Rules
- Classification Test Metrics

You can also compare classification test metrics.

The tables or views can be used by any application that can consume Oracle tables or views. You can publish results using tools such as BI-EE dashboards or OracleBI Discoverer. You can incorporate mining results, such as apply results, into applications created using Oracle Application Express, Oracle JDeveloper, or Oracle SQL Developer.

For requirements, see Publish as Database Table Requirements.

Follow these steps to publish data mining results to OracleBI Discoverer:

1. Install required BI and OracleBI Discoverer components.
2. Create a new EUL using OracleBI Discoverer.
3. Register the Oracle Data Miner Gateway with the EUL.
4. Use Oracle Data Miner to publish results to OracleBI Discoverer.
5. Add Oracle Data Miner gateway objects as folders in a business area using OracleBI Discoverer Administration.

### Automated Data Mining

Oracle Data Miner include the automated data mining of DBMS_PREDICTIVE_ANALYTICS described at the end of What’s New in Oracle Data Mining 10.2?. Oracle Data Miner includes the following new wizards:

- Data | Explain
- Data | Predict

### Oracle Data Miner PL/SQL Code Generator

Oracle Data Miner allows you to generate a PL/SQL package based on one or more activities. The generated code allows programmers to easily integrate functionality developed in Data Miner within a separate application. The code generated uses PL/SQL and SQL only. Oracle Data Miner does not generate Java code; however, the generated PL/SQL packages can be called from a Java program using JDBC.

Oracle Data Miner includes Code Generator extensions to Oracle JDeveloper and to Oracle SQL Developer. These extensions allow the generated packages to be installed directly into the database. Both JDeveloper and SQL Developer have features that allow users to easily test and debug PL/SQL packages, further simplifying application integration.

For information about installing these extensions, see Oracle Data Miner Code Generator Install and Uninstall.

#### Oracle Data Miner PL/SQL Code Generator Documentation

Detailed information about the Code Generator is in the online help for Data Miner and the Code Generator Extension; search for "code generator" to find the topics.

If the Code Generator extension to Oracle JDeveloper or to Oracle SQL Developer is installed, the documentation for Code Generator is part of the online help for JDeveloper or SQL Developer. To see the help, go to Help | About, select Contents; expand Oracle Data Miner PL/SQL Code Generator to see the documentation. The topic Code Generation Example shows how to generate and execute code for a simple apply activity.

### Model Wizards Removed

The model build, apply, and test wizard are no longer supported. The only way to build, apply, or test a model using Oracle Data Miner is to use a mining activity.

## What’s New in Oracle Data Mining?

The Oracle Data Mining 10g Release 2 (10.2) includes the following new algorithms and features:

- Decision Tree, a classification algorithm that always returns rules
- Revised Java interface compliant with the Java Data Mining (JDM) standard
- Native model import and export between different Oracle 10.2 instances
- One-class Support Vector Machine (SVM) classifiers for anomaly detection
- Predictive Analytics to automate the later stages of certain data mining problems

Models built using the Oracle Data Mining 10.1 Java interface are not compatible with models built using the Oracle Data Mining 10.2 Java interface. There is no automatic way to migrate Oracle Data Mining programs written using the Oracle Data Mining 10.1 Java interface to programs that use the Oracle Data Mining 10.2 Java interface. Models built using the Oracle Data Mining 10.2 PL/SQL interface and the Oracle Data Mining 10.2 Java interface are compatible.

Data mining models may need to be moved between Oracle databases or schemas. For example, data mining specialists may build and test data mining models on one dedicated system. After the models are built and tested, selected models may be deployed to another system used by applications. Because the system where the models are developed and the system where the models are deployed usually do not share the same database, the model must be exported from the system where it was developed and then imported to system where it will be used by applications.

Anomaly Detection models use the one-class SVM algorithm to build models when there are no counterexamples.

Predictive Analytics is based on the PL/SQL package DBMS_PREDICTIVE_ANALYTICS that automates the later stages of data mining; it provides the following functionality:

- Explain to rank attributes in order of influence in explaining a target column
- Predict to predict the value of a target attribute (categorical or numerical)

For more information about the new features, see Oracle Data Mining Documentation.

### Oracle Data Mining Documentation

Oracle Data Mining 10g Release 2 (10.2) documentation is part of the Oracle Database 10g Release 2 Documentation Library. To find Oracle Data Mining documentation, view or download the library; then click the Data Warehousing tab.

## Oracle Data Miner Tutorial

The tutorial for Oracle Data Miner 10.2 is available for download at Oracle Data Miner downloads page.

This tutorial is based on Oracle Data Miner 10.2.0.3; some screens for Oracle Data Miner 10.2.0.4.1 may be slightly different. The tutorial does not describe text mining.

In addition to the discussion in the tutorial, the online help for Oracle Data Miner contains an example that illustrates code generation for an apply activity.

The online help for Oracle Data Miner contains a text mining tutorial that illustrates basic text mining. To see the tutorial go to Help | Help Contents | Text Mining Tutorial.

## How to Start Oracle Data Miner

Start Oracle Data Miner as follows:

- On Microsoft Windows systems, double-click `data_miner_dir\bin\odminerw.exe`, where `data_miner_dir` is the folder where Oracle Data Miner is installed.

  Note: `odminer.exe` (without the w in its name) displays a console window that can be used for troubleshooting.

- On UNIX and Linux systems, run the script `odminer` in the directory `data_miner_dir/bin`, where `data_miner_dir` is the directory where Oracle Data Miner is installed.
- On Mac OS X, open a terminal and run the script `odminer` in the directory where Oracle Data Miner is installed. For example, if Data Miner is installed in `/Applications/odminer`, type

      cd /Applications/odminer/bin
      ./odminer &

### Define a Database Connection

When you start Oracle Data Miner for the first time, you must define a database connection.

Note: The user name and password that you specify when you define the connection must satisfy the requirements of Oracle Data Mining. Oracle Data Mining requires a small number of database permissions, plus `SELECT` access to the tables containing data for analysis. For details, see the Oracle Data Mining Administrator’s Guide.

The first time that you start Oracle Data Miner, a dialog appears asking for the following information:

- Connection Name, the name of the connection
- User, the name of the Oracle Data Mining user schema where data mining will take place.
- Password, the Oracle Data Mining user password.
- Save Password, a check box to indicate if the password is saved. If the password is not saved, it must be entered whenever a connection is made.
- Host, the system where Oracle Data Mining is installed.
- Port, the port number for the connection, for example `1521`.
- SID, the SID for the database where Oracle Data Mining is installed, for example `orcl`.
- Service Name, the service name for the database where Oracle Data Mining is installed.

  Note: You must specify either the SID or the Service Name; you cannot specify both.

Click OK when you finish the definition. You are returned to the Choose Connection dialog. You can now select the connection that you just defined from the drop down box.

You may need to contact your Oracle Data Mining DBA for this information.

You can define additional connections and edit existing ones:

- To define a new connection, click New in the Choose Connection dialog.
- To edit an existing connection, select the connection in the Connection drop down that you want to edit, and click Edit.

If Data Miner is running, you can manage (create, edit, and delete) database connections on the Connections tab of Tools | Preferences.

## Oracle Data Miner Install and Uninstall

Oracle Data Miner does not require an installer; to install Data Miner, you simply unzip the download.

Before you can use Oracle Data Miner, you must connect to an appropriate account in an Oracle 10g Release 2 database. Before you can connect, you must install Oracle Data Mining 10g Release 2 and create at least one user account for data mining. For information about how to do this, see Oracle Data Mining Administrator’s Guide and the installation instructions for the platform that you are using.

Before you install Oracle Data Miner make sure that the requirements described in Oracle Data Miner Requirements are satisfied.

### Oracle Data Miner Requirements

Oracle Data Miner requires the following:

- The Data Mining option to Oracle 10g Release 2 (10.2) Enterprise Edition must be installed. Data Miner 10.2.0.4.1 works with Oracle Data Mining 10.2.0.1, 10.2.0.2, and 10.2.0.3. (The Data Mining option is included by default in Oracle Database Enterprise Edition.)

  Warning: Do not install the Data Mining Scoring Engine. The Data Mining Scoring Engine does not allow you to build models. If you accidentally install the Scoring Engine, you must remove it and install Oracle Data Mining. See the Oracle Data Mining Administrator's Guide for directions.

- Any user of the Oracle Database must have a user name and password. Oracle Data Mining requires a small number of database privileges, plus `SELECT` access to the tables containing data for analysis; for a detailed list of privileges, see Required Privileges.
- On all platforms, you must have JDK 1.5. If you don't have the correct version of Java installed, you can obtain it from http://www.javasoft.com. For Mac OS, see Oracle Data Miner Requirements for Mac OS X.
- The version of the Oracle Data Mining Java API used by Data Miner is 10.2.0.3.
- If you wish to use the Oracle Data Mining sample programs, you must install them from the Companion CD, as described in Oracle Data Mining Administrator’s Guide.

Oracle Data Miner and Oracle Data Mining do not have to be installed on the same system. For example, you could install Oracle Data Mining on a system running UNIX and Oracle Data Miner on a PC running Microsoft Windows XP.

here are additional requirements for special purposes:

- Oracle Data Miner Requirements for Mac OS X
- Text Mining Requirements
- Publish as Database Table Requirements

#### Required Privileges

Oracle Data Miner requires following system privileges:

- `CREATE JOB`
- `CREATE TYPE`
- `CREATE SESSION`
- `CREATE TABLE`
- `CREATE SEQUENCE`
- `CREATE VIEW`
- `CREATE SYNONYM`
- `CREATE PROCEDURE`
- `EXECUTE ON ctxsys.ctx_ddl`, required for text mining only. If not available, text mining is disabled.
- `SELECT` privileges on the data being mined

The privileges required by Oracle Data Miner are the same as the privileges required for Oracle Data Mining. See Oracle Data Mining Administrator's Guide for details about how to create a user with these privileges.

`CREATE PROCEDURE` is satisfied by `CREATE ANY PROCEDURE`. `EXECUTE ON ctxsys.ctx_ddl` is satisfied by `EXECUTE ANY PROCEDURE`.

Oracle Data Miner searches for privileges by searching for direct grants to the user as well as roles assigned to a user. Oracle Data Miner searches one level deep within a role. For example, suppose that the role `ANALYST` includes the role `ODM_USER`; if the privileges are granted in the `ODM_USER` role (which is "one level down" from the role `ANALYST`), Oracle Data Miner will find them; if the privileges are defined in a role included in `ODM_USER`, they will not be found.

### Oracle Data Miner Requirements for Mac OS X

Oracle Data Miner has the following requirements for Mac OS X:

- Mac OS X 10.4.6 or higher.
- Java JRE 1.5 or higher. (Mac OS 10.5 comes with Java 1.5 preinstalled.) You can download Java JRE for Mac from http://www.apple.com.

Oracle Data Mining 10.2 cannot be installed directly on Mac OS X at this time. Therefore, you may have to connect to an Oracle database running on some other platform.

One solution it to use Parallels Desktop for Mac to create a Microsoft Windows virtual machine on your MacIntosh, and install the Microsoft Windows version of Oracle 10.2 EE with the Data Mining option on the Windows virtual machine; you can connect to the Oracle database running in the Microsoft Windows virtual machine. Another solution is to connect to Oracle 10.2 EE with the Data Mining Option on some other machine running Microsoft Windows, UNIX, or Linux.

### Text Mining Requirements

The following restrictions apply to text mining using Oracle Data Miner:

- You can include one text column in a mining operation.
- The text column must reside in a table, not a view. A mining activity will create a table, if necessary.
- The text column must have data type `CLOB`, `BLOB`, `BFILE`, `LONG`, `VARCHAR2`, `XMLType`, `CHAR`, `RAW`, or `LONG RAW`.
- You must have Oracle Text installed on the Server. Oracle Text is required for indexing text columns. Oracle Text is part of Oracle 10g server; the required `INDEXTYPE` `ctxsys.context` is part of the Seed Database. Oracle Text is installed by default when you install the Oracle Database. If you explicitly exclude it, you will not be able to use Oracle Data Miner for text mining.

### Publish as Database Table Requirements

If you just want to publish data mining results as Oracle Database tables or views, use the Oracle Data Miner menu selection Tools | Publish as Database Table. No additional software is required to publish the selected object; however, it may be necessary to configure the program that consumes the table. For detailed requirements for publishing to OracleBI Discover, see Publish to OracleBI Discoverer.

#### Publish to OracleBI Discoverer

If you intend to use published mining results in OracleBI Discoverer, the following software is required; in each case click the link to download the software:

- Oracle BI Discoverer 10.1.2.0.0 or higher
- Oracle Developer Suite 10.1.2.0.0 or higher: OracleBI Discoverer Administrator is required; other components of the suite are optional.
- Patch 4430506 for OracleBI Discoverer Administrator, available from Oracle MetaLink; if this patch is not installed, the gateway will not work.

After you install the software, register the Oracle Data Miner Discoverer Gateway in the EUL to be able to access the published data mining results from a Discoverer Administrator:

1. If an EUL does not exist, create a new EUL.

   These links describe creating an a EUL in two different cases:

   - Create an EUL for an existing database user
   - Create an EUL in a new database user

2. Register the Oracle Data Miner Discoverer Gateway with the EUL:

   Execute the following SQL script in the EUL user to register the Oracle Data Miner Discoverer Gateway with the EUL:

       -- registration script
       insert into EUL5_GATEWAYS(
             gw_id,             -- Gateway ID
             gw_type,           -- Type of Gateway
             gw_gateway_name,   -- Name of Gateway
             gw_product_name,   -- Name of the product
             gw_description,    -- Description of the gateway
             egw_version,       -- version of the gateway
             egw_database_link, -- For remote DB provide dblink
             egw_schema,        -- Gateway owner
             egw_sql_paradigm,  -- SQL paradigm
             gw_element_state,  -- element state
             gw_created_by,     -- who created this gateway
             gw_created_date,   -- when it was created
             gw_updated_by,     -- who updated this gateway
             gw_updated_date,   -- when it was updated
             notm
             )
               values
                          (
                    EUL5_ID_SEQ.NEXTVAL,
                                'EGW',
                                'ODMr 10.2 Discoverer Gateway',
                    'Oracle Data Mining',
                                'This gateway provides data mining results accessible to OracleBI',
                                '1.1',
                                NULL, -- dblink if dmuser is in remote
                    'DMUSER', -- Change to the schema as needed
                    'OBJECT',
                                0,
                                USER,
                                SYSDATE,
                                USER,
                                SYSDATE,
                                0
                               )

### Install Steps

Oracle Data Miner does not require an installer. To install Oracle Data Miner, you download a zip archive and unzip it. You must have an unzip tool.

You can have multiple versions of Data Miner installed on the same system. For example, you can have Data Miner 10.2 and Data Miner 11.1 installed on the same system.

It is not necessary to uninstall existing versions of Data Miner before you install new versions. However, you should unzip different versions of Data Miner into different directories.

Exact installation steps depend on the target operating system; you can install Oracle Data Miner on the following operating systems:

- Microsoft Windows
- UNIX and Linux
- Mac OS X

#### Install on Microsoft Windows

Data Miner does not require an installer. To install Data Miner, you need an unzip tool. If your system does not include an unzip tool, you can download a free, cross-platform unzip tool, Info-Zip, available at http://www.info-zip.org/.

Note: Do not install this Data Miner release into any existing `ORACLE_HOME`. You will not be able to uninstall it using Oracle Universal Installer.

Follow these steps to install Oracle Data Miner on Microsoft Windows:

1. Oracle Data Miner on Microsoft Windows requires Java JDK 1.5. To check the version of Java, use the command `java -version` in a Command Prompt window.
2. Create a new directory for the new version of Oracle Data Miner. It is not necessary to uninstall any existing versions of Data Miner.
3. Download `odminer102.zip`.
4. Unzip the entire contents of `odminer102.zip` to the desired directory, for example, unzip to `C:\odminer`.
5. Run (double click) `data_miner_dir\bin\odminerw.exe`, where `data_miner_dir` is the folder where Oracle Data Miner is installed. For example, execute `C:\odminer\bin\odminerw.exe`
6. Define a connection as described in Define a Database Connection.

Note: `odminer.exe` (without the w in its name) displays a console window that can be used for troubleshooting.

#### Install on UNIX or Linux

Data Miner does not require an installer. To install Data Miner, you need an unzip tool. If your system does not include an unzip tool, you can download a free, cross-platform unzip tool, Info-Zip, available at http://www.info-zip.org/.

Note: Do not install this Data Miner release into any existing `ORACLE_HOME`. You will not be able to uninstall it using Oracle Universal Installer.

Follow these steps to install Data Miner on UNIX or Linux:

1. Oracle Data Miner on UNIX or Linux requires Java JDK 1.5. To check the version of Java, use the command `java -version`.
2. Create a new directory for the new version of Oracle Data Miner. It is not necessary to uninstall any existing versions of Data Miner.
3. Download `odminer102.zip`.
4. Download `odminer102.zip`.
5. Unzip `odminer102.zip` to the desired Oracle Data Miner root directory; for example, use the following command to unzip the file to the directory `odminer` in the current working directory using the `unzip` command `unzip odminer102.zip -d odminer`. This command creates the directory `odminer` (in the current working directory) and extracts the archive into it.
6. To start Oracle Data Miner, run the script `odminer` in the directory `data_miner_dir/bin`, where `data_miner_dir` is the directory where Oracle Data Miner is installed. If the script is not executable, reset the permissions: `chmod +x odminer`
7. Define a connection as described in Define a Database Connection.

#### Install on Mac OS

Data Miner does not require an installer.

Note: Do not install this Data Miner release into any existing `ORACLE_HOME`. You will not be able to uninstall it using Oracle Universal Installer.

Follow these steps to install Data Miner on Mac OS X:

1. Check that you have the required version of Java.
2. Create a new directory for the new version of Oracle Data Miner. It is not necessary to uninstall any existing versions of Data Miner.
3. Download `odminer102.zip`.
4. Unzip `odminer102.zip` to the desired Oracle Data Miner root directory; you can use StuffIt Expander or similar software to unzip the downloaded file.
5. To start Oracle Data Miner, open a terminal and run the script `odminer` in the directory where Oracle Data Miner is installed. For example, if Data Miner is installed in `/Applications/odminer`, type

       cd /Applications/odminer/bin
       ./odminer &

6. Define a connection as described in Define a Database Connection.

### Data Miner Uninstall

It is not necessary to uninstall existing versions of Data Miner before you install new versions. However, you should unzip different versions of Data Miner into different directories.

If you wish to uninstall Oracle Data Miner on any platform, delete `data_miner_dir`, the directory where Oracle Data Miner is installed. Make sure that you delete all of the subdirectories of `data_miner_dir`.

## Oracle Data Miner Code Generator Install and Uninstall

Oracle Data Miner includes a wizard and extensions for Oracle JDeveloper and for Oracle SQL Developer that support using generated code in applications.

### Oracle Data Miner PL/SQL Code Generator Extension Requirements

The Code Generator Extension requires Oracle JDeveloper 10.1.3.3 or Oracle SQL Developer 1.5.1 (or a patch release of 1.5.1, such as 1.5.2).

The requirements for installing the Oracle Data Miner PL/SQL Code Generator Extension are the same as those for Oracle Data Miner 10.2.0.4.

Certain tasks have additional requirements, as follows:

- If you plan to compile and execute the generated code, Oracle Data Mining 10.2 must be available in the database where the code executes.
- If you generate code that supports the Oracle Workflow API, Oracle Workflow must be installed and certain grants must be made. Generated code works with any version of Oracle Workflow that runs on Oracle 10.2.
- If you plan to use JDeveloper or SQL Developer to debug programs using generated code, you must have the following system privileges:
  - `DEBUG ANY PROCEDURE`
  - `DEBUG CONNECT SESSION`

### Code Generator Extension Install Using a File

Follow these steps to install the Oracle Data Miner PL/SQL Code Generator Extension for either Oracle JDeveloper or Oracle SQL Developer:

1. Download `ODMrExtJDev.zip` for JDeveloper or `ODMrExtSQLDev15.zip` for SQL Developer and save it into a temporary location; do not save it in either the `jdev_install\jdev\extensions` or `sqldev_install\sqldeveloper\jdev\extensions` directory.
2. Launch JDeveloper or SQL Developer.
3. Select Help | Check for Updates
4. Click Next on the Welcome to Check for Updates Wizard page.
5. In Step 1 of 3: Source, select Install from Local File and then select the Browse and locate `ODMrExtJDev.zip` for JDEveloper or `ODMrExtSQLDev15.zip`. Click Next, and finish the wizard.
6. The Confirm Restart dialog is displayed; select Yes.
7. The Migrate User Settings dialog is displayed; select No.
8. JDeveloper or SQL Developer is restarted with the Data Mining Code Generator Extension enabled.
9. Start the wizard as described in Using the Code Generator Extension.

### Code Generator Extension Install Using the Update Center

Note: If the extensions that you wish to install are not in the update center, install them using the directions in Code Generator Extension Install Using a File.

Follow these steps to install the extension using the Update Center:

1. Launch JDeveloper or SQL Developer.
2. Select Help | Check for Updates
3. Click Next on the Welcome to Check for Updates Wizard page.
4. In Step 1 of 3: Source, select the Official Oracle Extensions and Updates update center, and click Next.
5. Select Oracle Data Mining PL/SQL Package.
6. Follow the directions in the wizard to install the extension. The installation will require a restart of JDeveloper or SQL Developer.
7. The Confirm Restart dialog is displayed; select Yes.
8. The Migrate User Settings dialog is displayed; select No.
9. JDeveloper or SQL Developer is restarted with the Data Mining Code Generator Extension enabled.
10. Start the wizard as described in Using the Code Generator Extension.

For a brief tutorial illustrating how to generate and execute code for an apply activity, see the Code Generation Example in Oracle Data Miner Help Contents.

### Using the Code Generator Extension

To verify that the latest version of the Code Generator extension is installed, select Help | About in JDeveloper or SQL Developer and look for the following entry:

`Oracle Data Mining PL/SQL Package oracle.dmt.dm4j.extension.codegenerator Version Number Loaded`

Follow these steps to generate code for an already-built activity:

- In JDeveloper connect to a database, select a schema, and select File | New. Data Mining PL/SQL Package is listed in the New Gallery in the Database Tier under Database Objects.
- In SQL Developer, select a connection to a Data Mining Server, connect to it, and then select File | New | Database Tier | Database Objects; Data Mining PL/SQL Package is one of the items.
- In either case, click OK to launch the code generator wizard.

For a brief tutorial illustrating how to generate and execute code for an apply activity, see the Code Generation Example in Oracle Data Miner Help Contents. For more examples, see the Oracle Data Miner Tutorial.

### Code Generator Extension Disable

Follow these steps to disable Oracle Data Miner PL/SQL Code Generator Extension from either Oracle SQL Developer or JDeveloper:

1. Go to the Tools menu and select Preferences.
2. Select Extensions in the tree selection on the left of the Preferences Dialog.
3. Unselect (uncheck) Data Mining PL/SQL Package and click OK.
4. The Confirm Restart dialog will be displayed; select Yes.
5. To enable again, simply repeat these steps, but select (check) the extension.

## Oracle Data Miner Notes

The following notes apply to Oracle Data Miner:

1. Oracle Data Mining 10g Release 2 supports two interfaces, a Java interface and a PL/SQL interface. The Oracle Data Mining 10.2 Java and PL/SQL interfaces are compatible; for example, you can use the Java interface to apply a model built using the PL/SQL interface. Oracle Data Miner can be used with mining objects created using either the Oracle Data Mining 10.2 Java or the Oracle Data Mining 10.2 PL/SQL interface.
2. File Import requires SQL*Loader. If you install the Administrator installation type of Oracle Administrative Client, SQL*Loader is installed. If you have either the Database Server or the Database Client (with the Administrator option) installed on the same system as Data Miner, then SQL*Loader is in `ORACLE_HOME\BIN\sqldr.exe`. You specify the location of SQL*Loader in Tools | Preferences in Data Miner.
3. The user name that you specify when you connect must be the name of a database user account with the appropriate permissions. See Oracle Data Mining Administrator’s Guide for information about how to create such accounts.
4. If you cannot build models, the Data Mining Scoring Engine may be installed instead of the Oracle Data Mining Option. The Data Mining Scoring Engine does not allow you to build models. To see if the Scoring Engine is installed, follow these steps:
   1. Start SQL*Plus and log in as `SYSDBA`.
   2. Execute the following query:

      `SELECT VALUE FROM V$OPTION WHERE PARAMETER = 'Data Mining Scoring Engine';`

   3. If the query returns the following:

          VALUE
          ----------------------------------------------------------------
          TRUE

      then the Scoring Option is installed, and the Data Mining Option is not installed. You must install the Data Mining Option. See the Oracle Data Mining Administrator's Guide for directions.
5. Data Miner ships in English only.
6. Do not delete any tables or views with names that start with `DM4J$`. All such tables and views contain metadata used by Oracle Data Miner. If you delete any of these tables or views, Oracle Data Miner will not function and no recovery is possible. In addition, Oracle Data Mining creates tables in the user's schema with names that start with `DM$`; do not delete any of these files, either.
7. On high resolution wide monitors, you may find fonts problems. If this is the case, try replacing the JRE packaged with Data Miner with a more recent JRE, as follows:
   1. Download the latest version of Java Runtime Environment (JRE) 6 from http://developers.sun.com/downloads/top.jsp. Install the downloaded file.
   2. Go to `data_miner_dir`, the directory where Data Miner is installed.
   3. Rename the `jre` directory to `jrebackup`.
   4. Copy the downloaded JRE to `data_miner_dir`. If you installed the downloaded JRE to the default location for Microsoft Windows, the JRE directory is `C:\Program Files\Java\jre1.6.0_rel`, for example, `C:\Program Files\Java\jre1.6.0_07`, if you downloaded version 7.
   5. Rename the copied JRE folder to `jre`, for example, rename `jre1.6.0_07` to `jre`.

## Oracle Data Miner Bugs

The following are Oracle Data Miner bugs and Oracle Data Mining bugs that affect Oracle Data Miner:

1. Performance issue with displaying histograms on a large data set using Data Summarization Viewer. This can be avoided by either sampling the data or viewing the data within the Build Mining Activity.
2. The Mapping Name used for transaction column data mapping cannot be a mixed-case name.
3. O-Cluster does not support VARCHAR2 case IDs.
4. O-Cluster and Decision Tree do not support nested columns.
5. Anomaly Detection model build fails if the nested column name is lowercase.

Copyright © 2006, 2008, Oracle. All rights reserved.

Oracle, JD Edwards, PeopleSoft, and Siebel are registered trademarks of Oracle Corporation and/or its affiliates. Other names may be trademarks of their respective owners.