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Oracle Data Mining Concepts
10g Release 1 (10.1)

Part Number B10698-01
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A
ODM Interface Comparison

The Java and PL/SQL interfaces for Oracle Data Mining (ODM) provide similar functionality; however, they are not identical. They are aimed at different audiences; they support different features on a detailed level; and they must be used differently in different programming environments. This appendix compares the two interfaces.

A.1 Target Users of the ODM Interfaces

The two interfaces are aimed at different audiences, as follows:

A.2 Feature Comparison of the ODM Interfaces

Table A-1 summarizes the differences in features between the two data mining interfaces.

Table A-1 ODM Java and PL/SQL Interface Feature Comparison
Feature ODM Java Interface DBMS_DATA_MINING Interface

Operation mode

Asynchronous.

Synchronous.

If asynchronous execution is required, use other Oracle database features like unified scheduler

Algorithms

ODM k-means algorithm.

Different version of k-means algorithm; faster, handles sparse data, supports new distance metrics (cosine and fast cosine), handles categorical and numerical attributes, doesn't require binning (instead it normalizes numeric attributes)

O-Cluster not supported

Model build specification

Based in ODM classes: LAD (data location), PDS (format of input data), MFS (function settings), MAS (algorithm settings)

Data location (schema) is passed in the argument list (default is user schema); mining function is passed in argument list; settings (function and algorithm) are passed in a single optional table

Settings

Provided through Java objects MAS (optional) and MFS.

Provided through an optional settings table.

Default settings

Available for algorithms?

Available for function and algorithm.

Attribute form type

LDS (explicit or convenience function)

Automatically inferred from column data type; form types can be modified using views

Location of input data and result tables

LAD (Java object)

Provided in the argument list as schema information; default is user schema

Input data structure

Supports both single-record case both single-record case (as a conventional relational table input) and multi-record case (as a table input in "transactional format")

Supports both single-record case (as a conventional relational table input) and multi-record case (as a conventional relational table with nested table columns representing association of multiple attributes of the same kind with the same case identifier ("wide data")

Model apply (data scoring)

Flexible filtering specification

Apply interface is provided; a separate interface to rank apply accepts a cost matrix input to enable results generation on the basis of cost

Model evaluation

Confusion matrix and lift metrics for classification, tightly coupled with models for maximum ease of use

Provides a variety of evaluation metrics: confusion matrix, lift RMSE, and ROC. Not coupled with a model for maximum flexibility; allows use of different cost matrices at evaluation time and performance evaluation of non-ODM models

Transformations (data preparation)

Internal support for automatic binning and normalization. Other transformations must be performed as pre-processing.

All transformation must be performed as pre-processing. Normalization and binning are supported by DBMS_DATA_MINING_TRANSFORM

Model export and import

PMML export/import for Naive Bayes and Association models; no support for native format

Export and import of all models in native format; no support for PMML.

Model comparison (finding the best model)

Model Seeker builds multiple NB and ABN models and selects the "best" one

Not supported

Cross validation

Automatic for NB models

Not supported

A.3 The ODM Interfaces in Different Programming Environments

Table A-2 compares using the two interfaces in different programming environments.

Programming in XML programming in PL/SQL
Table A-2 ODM APIs in Programming Environments
Environment ODM Java interface ODM PL/SQL interface

Programming in PL/SQL

Package ODM routines as PL/SQL (Java Stored Procedures)

Use the ODM packages DBMS_DATA_MINING and DBMS_DATA_MINING_TRANSFORM.

Programming in Java

Use native calls.

Use JDBC to call the ODM PL/SQL packages.

Programming in OCI/C or OOCI/C++

Invoke PL/SQL (Java stored procedures) through OCIStatement() calls.

.Use the ODM packages DBMS_DATA_MINING and DBMS_DATA_MINING_TRANSFORM

Programming in Pro*C, COBOL, or FORTRAN

Invoke PL/SQL (Java stored procedures) using EXEC calls

Use standard EXEC SQL interface.

Programming in XML

JDeveloper9i (and the new JDK1.4 release) enable seamless Java/XML and generation of execution objects (SOAP).

NA