The PL/SQL API interface for Oracle Data Miner has had a number of new features. These are listed below along with the new API features added with the 11.1 release.
- Support for Native Transactional Data with Association Rules: you can build association rule models without first transforming the transactional data.
- SVM class weights specified with CLAS_WEIGHTS_TABLE_NAME: including the GLM class weights
- FORCE argument to DROP_MODEL: you can now force a drop model operation even if a serious system error has interrupted the model build process
- GET_MODEL_DETAILS_SVM has a new REVERSE_COEF parameter: you can obtain the transformed attribute coefficients used internally by an SVM model by setting the new REVERSE_COEF parameter to 1
11.1g API New Features
- Mining Model schema objects: previous releases, DM models were implemented as a collection of tables and metadata within the DMSYS schema. in 11.1 models are implemented as data dictionary objects in the SYS schema. A new set of DD views present DM models and their properties
- Automatic and Embedded Data Preparation: previously data preparation was the responsibility of the user. Now it can be automated
- Scoping of Nested Data: supports nested data types for both categorical and numerical data. Most algorithms require multi-record case data to the presented as columns of nested rows, each containing an attribute name/value pair. ODM processes each nested row as a separate attribute.
- Standardised Handling of Sparse Data & Missing Values: standardised across all algorithms.
- Generalised Linear Models: has a new algorithm and supports classification (logistic regression) and regression (linear regression)
- New SQL Data Mining Function: PREDICTION_BOUNDS has been introduced for Generalised Linear Models. This returns the confidence bounds on predicted values (regression models) or predicted probabilities (classification)
- Enhanced Support for Cost-Sensitive Decision Making: can be added or removed using DATA_MINING.ADD_COST_MATRIX and DBMS_DATA_MINING_REMOVE_COST_MATRIX.