Oracle Data Miner 10.2 supercedes Oracle Data Miner 10.1 and the Oracle Data Mining Components and Browser (DM4J).
Oracle Data Miner does not require the use of Oracle JDeveloper.
Oracle Data Miner Release 10.2 targets the data analyst. The user interface is designed to increase the analyst’s success rate in properly utilizing ODM algorithms in several ways:
The Oracle Data Miner supports many of the new Oracle Data Mining(ODM) 10.2 features. ODM 10.2 supports Decision Tree Models, one-class classifiers using Support Vector Machine, and a new Java interface that complies with the Java Data Mining (JDM) standard for data mining (JSR 73).
This section briefly describes new features of Oracle Data Miner 10.2.
Oracle Data Miner supports the following
A Mining Activity is a step-by-step guide for model build or apply. 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.
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 or an apply activity.
The Mining Activities in Oracle Data Miner 10.2 completely automate data mining.
Names of tables and views and for mining objects may have mixed case. Such names must be enclosed in quotation marks.
Oracle Data Miner has revised versions of the Sample and Stratified Sample transformation wizards that are easier to use.
Oracle Data Miner includes model viewers for Anomaly Detection models. There is also a view for regression test metrics.
Oracle Data Miner supports Receiver Operator Characteristics (ROC) for classification models.
Oracle Data Miner provides residual plots for regression models.
Copyright © 2005, Oracle. All rights reserved.