May 2009
Compatibility with Previous Releases of Oracle Data Miner
Oracle Data Miner 11.1 Overview
What’s New in Oracle Data Mining?
Oracle Data Mining Documentation
How to Start Oracle Data Miner
Oracle Data Miner Install and Uninstall
Oracle Data Miner Requirements
Oracle Data Miner Requirements for Mac OS X
Oracle Data Miner Code Generator Install and Uninstall
Oracle Data Miner Code Generator Extension Requirements
Code Generator Extension Install Using a File
Code Generator Extension Install Using the Update Center
Using the Code Generator Extension
Code Generator Extension Disable
Oracle Data Miner Bugs Fixed in This Release
Oracle Data Miner 11.1.0.2 is a patch release of Oracle Data Miner 11.1.
Oracle Data Miner 11.1 is the graphical user interface for Oracle Data Mining 11.1; Oracle Data Miner replaces all previous graphical user interfaces to Oracle Data Mining, including Oracle Data Miner 10.1, Oracle Data Miner 10.2, 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 10g Release 2 database using Oracle Data Miner 11.1; to connect to an Oracle 10g Release 2 database, use Oracle Data Miner 10.2.
This document provides a brief overview of new features of Oracle Data Mining 11g and Oracle Data Miner 11.1, along with installation instructions for Oracle Data Miner.
These release notes describe how to install Oracle Data Miner on Mac OS.
Models built using Oracle Data Miner 10.1 or Oracle Data Miner 10.2 cannot be used with Oracle Data Miner 11.1.
Oracle Data Miner requires Oracle 11g Release 1; you cannot connect to any other version of Oracle Database. Any patch version of Oracle 11g Release 1 is compatible with Oracle Data Miner.
You can have both Oracle Data Miner 10.2 and Oracle Data Miner 11.1 installed on the same system; each version of Data Miner connects to a different version of Oracle.
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 supports the new Oracle Data Mining 11g 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 11.1:
Oracle Data Mining 11g introduces a new algorithm Generalized Linear Models (GLM). GLM supports two mining functions: classification (logistic regression) and regression (linear regression).
Oracle Data Mining supports nested data types for both categorical and numerical data. Multi-record case data must be transformed to nested columns for mining.
Note: In Oracle Data Mining 11g, Decision Tree and O-Cluster algorithms do not support nested data.
Handling of sparse data and missing values has been standardized across algorithms in Oracle Data Mining 11g. Data is sparse when a high percentage (for example, 90%) of the cells are empty but all the values are assumed to be known. This is the case in market basket data; for example in a supermarket, you have thousands of products, but a customer only purchases a small number at any given time. When some cells are empty, and their values are not known, they are assumed to be missing at random. Oracle Data Mining assumes that missing data in a nested column is a sparse representation, and assumes that missing data in a non-nested column is missing at random.
In Oracle Data Mining 11g, the Adaptive Bayes Network (ABN) classification algorithm is deprecated. Oracle Data Miner 11.1.0.2 does not support building models using the ABN algorithm.
If you need to create a classification model that provides rules for its predictions, a simple solution would be to use the Decision Tree algorithm.
Oracle Data Mining 11g Release 1 (11.1), the server that Data Miner connects to, includes the following new algorithms and features:
For information about the new features, see Oracle Data Mining Documentation.
Oracle Data Mining 11g Release 1 (11.1) documentation is part of the Oracle Database 11g Release 1 (11.1) Documentation Library. To find Oracle Data Mining documentation, view or download the library; then click the Data Warehousing and Business Intelligence link. Oracle Data Mining documentation is also available at Oracle Data Mining Documentation.
The tutorial for Oracle Data Miner 11.1 is available for download at Oracle Data Miner downloads page.
The tutorial is based on Oracle Data Miner 10.2.0.3; some screens for Oracle Data Miner 11.1.0.2 may be slightly different. The tutorial does not describe text mining.
For information about installing Oracle Data Mining 11.1, see Oracle Data Mining Administrator’s Guide.
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.
Start Oracle Data Miner as follows:
data_miner_dir\bin\odminerw.exe
,
where data_miner_dir
is the folder where Oracle Data Miner is
installed.odminer
in the directory data_miner_dir/bin
,
where data_miner_dir
is the directory where Oracle Data Miner
is installed.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 &
Note: odminer.exe
(without the w in its
name) displays a console window that can be used for troubleshooting.
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:
1521
.orcl
.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:
If Data Miner is running, you can manage (create, edit, and delete) database connections on the Connections tab of Tools | Preferences.
Installation instructions depend on the target operating system; you can install Oracle Data Miner on the following operating systems:
Before you can use Oracle Data Miner, you must connect to an appropriate account in an Oracle 11gRelease 1 (11.1) database. Before you can connect, you must install Oracle Data Mining 11g Release 1 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.
The following describe Oracle Data Miner requirements. These requirements must be satisfied before you try to build models.
SELECT
access to the tables containing data for analysis; for a
detailed list of privileges, see Required Privileges.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.
There are additional requirements for special purposes:
Oracle Data Miner requires following system privileges:
CREATE MINING MODEL
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 minedThe 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 MINING MODEL
is a new requirement for Oracle Data Mining 11.1.
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 has the following requirements for Mac OS X:
Oracle Data Mining 11.1 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 11.1 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 11.1 EE with the Data Mining Option on some other machine running Microsoft Windows, UNIX, or Linux.
The following restrictions apply to text mining using Oracle Data Miner:
CLOB
, BLOB
,
BFILE
, LONG
,
VARCHAR2
, XMLType
, CHAR
, RAW
,
or LONG RAW
.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.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:
java -version
in a Command Prompt window.odminer110.zip
.odminer110.zip
to the
desired Oracle Data Miner root directory, for example, unzip to C:\odminer
.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
Note: odminer.exe
(without the w in its
name) displays a console window that can be used for troubleshooting.
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:
java -version
.odminer110.zip
.odminer110.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 odminer110.zip -d odminer
.
This command creates the directory odminer
(in the
current working directory) and extracts the archive into it.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
Data Miner does not require an installer.
Follow these steps to install data Miner on Mac OS X:
odminer110.zip
.odminer110.zip
to the desired Oracle Data Miner
root directory; you can use StuffIt Expander or similar software to unzip the
downloaded file.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 &
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 includes a wizard and extensions for Oracle JDeveloper and for Oracle SQL Developer that support using generated code in applications. Follow these steps to generate code:
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 11.1.
Certain tasks have additional requirements, as follows:
DEBUG ANY PROCEDURE
DEBUG CONNECT SESSION
Follow these steps to install the Oracle Data Miner PL/SQL Code Generator Extension for either Oracle JDeveloper or Oracle SQL Developer:
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.ODMrExtJDev.zip
for
JDEveloper or ODMrExtSQLDev15.zip
.
Click Next, and finish the wizard. 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:
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:
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 chapter 15 of the Oracle Data Miner Tutorial.
Follow these steps to disable Oracle Data Miner PL/SQL Code Generator Extension from either Oracle SQL Developer or JDeveloper:
The following notes apply to Oracle Data Miner:
C:\app\user\product\11.1.0\client_client_num\BIN\sqlldr.exe
.
You specify the location of SQL*Loader in
Tools | Preferences in Data Miner.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. data_miner_dir
, the directory where Data Miner is installed.jre
directory to jrebackup
.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.jre
, for example,
rename jre1.6.0_07
to jre
.The following Oracle Data Miner bugs are fixed in this version:
The following are Oracle Data Miner bugs and Oracle Data Mining bugs that affect Oracle Data Miner:
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