| IKODA (Intelligent KnOwledge Discovery
Assistant) utilizes "data aware" visualization techniques that
lie atop a unified and persistent knowledge representation and
provide a mapping between graphical objects and the underlying
data resources. This approach results in the ability to
perform direct manipulation operations such as drag-and-drop
transfer of data between tools and a unique capability to explore
data mining results. Unlike previous integrated KDD systems,
IKODA's visualizations act as interactive tools rather than
simple information displays. Specifically, IKODA's visualizations
of data mining results (e.g., decision trees and automatically
created data clusters) can be manipulated and used directly
to form new datasets that feed future data mining operations.
The resulting "recursive" knowledge discovery capability represents
a substantial step forward in reducing KDD tool complexity while
simultaneously increasing flexibility and efficacy.
The Predictive Model Markup
Language (PMML) is an XML-based language which provides
a quick and easy way to define and share predictive models
between applications. PMML's open text-based format
enables researchers and commercial users to carry out different
data mining tasks (e.g. train, test, apply, visualize) with
different tools and, if necessary, edit the model (as an XML
document) using a simple text editor. IKODA supports
a PMML interface that serves as an API to IKODA's data mining.
PMML
A general data mining solution is not always the best solution
to a domain-specific problem. Many users would like to utilize
the functionality of data mining algorithms but are not database
experts or statisticians. They want an interface that
uses the domain terminology and hides the complexity of the
data mining algorithms. The PMML interface makes it possible
to use IKODA as a data mining engine to power vertical solutions.
The data mining algorithms work behind the scenes of the customized
front-end and the user receives the results in the terms to
which they are accustomed.
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