Predictive Model Markup Language - PMML 4.0 and 4.1

PMML 4.0 and 4.1

The previous version of PMML, 4.0, was released on June 16, 2009.

Examples of new features included:

• Improved Pre-Processing Capabilities: Additions to built-in functions include a range of Boolean operations and an If-Then-Else function.

• Time Series Models: New exponential Smoothing models; also place holders for ARIMA, Seasonal Trend Decomposition, and Spectral density estimation, which are to be supported in the near future.

• Model Explanation: Saving of evaluation and model performance measures to the PMML file itself.

• Multiple Models: Capabilities for model composition, ensembles, and segmentation (e.g., combining of regression and decision trees).

• Extensions of Existing Elements: Addition of multi-class classification for Support Vector Machines, improved representation for Association Rules, and the addition of Cox Regression Models.

The latest version of PMML, 4.1, was released on December 31, 2011.

New features include:

• New model elements for representing Scorecards, k-Nearest Neighbors (KNN) and Baseline Models.

• Simplification of multiple models. In PMML 4.1, the same element is used to represent model segmentation, ensemble, and chaining.

• Overall definition of field scope and field names.

• A new attribute that identifies for each model element if the model is ready or not for production deployment.

• Enhanced post-processing capabilities (via the Output element).