XELOPES Library

The prudsys XELOPES library (eXtEnded Library fOr Prudsys Embedded Solutions) is an open business intelligence library based primarily on embedded Data Mining. It is an open application and can be used with practically any platform or data source. XELOPES is CWM-compatible, supports the current BI standards and can be combined with all prudsys products.

Areas of application

Integration of prudsys models into user applications: All prudsys Data Mining products (as well as products from other data mining providers) can export their Data Mining models as XML files in PMML format. The XELOPES library, as a part of your application, allows you to import PMML models to be used for new data as scoring or recommendation engines.

Integration of prudsys models into user applications:

The XELOPES library has powerful Data Mining algorithms that integrate easily into your application. The comprehensive design automates procedure parameter selection and therefore enables fully automatic usage. Integration of user Data Mining procedures: The XELOPES library enables quick integration of new Data Mining methods, which can access the complete framework of the library, including standards.

Universal

The XELOPES library expands the "emerging" Common Warehouse Metamodel (CWM) OMG standard and at the same time represents one of its first implementations. Like the CWM it is specified completely in UML and is therefore platform independent. Implementations for Java, C++ and C#, CORBA and web service interfaces are currently available. The universal mining input stream design allows the library to be applied to various data sources - from the main memory right through to files and databases. It is easy to program your own data access classes. This makes XELOPES completely independent of both programming language and data source types.

Standards supported

The design of XELOPES library is completely compatible with the CWM standard. The PMML data exchange format is extensively supported. Other supported BI standards are JMI and JOLAP. There are connectors for OLE DB for Data Mining as well as for various popular Data Mining libraries.

Architecture

Data import

Data sources for data mining access are uniformly modelled using the abstract class MiningInputStream. There are ready-to-use access classes for memories, databases and files including special formats like CSV, Excel and logs. Users can use add-ons to the MiningInputStream class to develop their own data access classes, specifically tailored to his own applications.

Analytical functions

The analytical functions of the XELOPES library are divided into three large packages: multidimensional, Data Mining and reinforcement learning.

The multidimensional package contains multidimensional selections, groupings and a complete OLAP engine. It thus represents an extremely lean implementation for database functions and OLAP.

The Data Mining package contains statistics with multidimensional grouping, decision and regression trees, neural networks, support vector machines, sparse grids, cluster methods, shopping basket analytics with taxonomies and sequence analysis. prudsys has the world's fastest Data Mining method in the areas of non-linear regression, shopping basket and sequence analytics and sequential shopping basket analysis

The reinforcement learning package contains various methods from the areas of dynamic programming and online learning. It also uses models from the Data Mining package for approximations.

Results and export

XELOPES stores its models in the CWM-class MiningModel, which can be serialised in various ways. In addition, the models can be exported in data mining standard formats like PMML.

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