ADAPA

:This article is about a decision engine. For the Babylonian and Summerian god of wisdom, see Adapa.
ADAPA is intrinsically a predictive decisioning platform. It combines the power of predictive analytics and business rules to facilitate the tasks of managing and designing automated decisioning systems.
Automated decisions
When first released, ADAPA (Adaptive Decision And Predictive Analytics) was purely a scoring engine, used to produce scores out of statistical models expressed in PMML (Predictive Model Markup Language) format. The later addition of a rules engine to its core enabled ADAPA users to combine rules and predictive models. This combination allows businesses to manage and design automated decisioning systems. In this way, ADAPA allows for the concretization of Enterprise Decision Management (EDM) solutions.
PMML support and predictive analytics
Predictive analytics comprises a series of modeling techniques which can be used to extract relevant patterns present in large amounts of data to better predict the future.
ADAPA is able to generate scores out of a variety of predictive modeling techniques expressed in PMML. PMML provides a standard way for the expression of predictive models. In this way, proprietary issues and incompatibilities are no longer a barrier to the exchange of models between applications.
Currently, ADAPA supports the following PMML elements:
* Decision Trees
* Neural Networks
* Clustering Models
* Naive Bayes Classifiers
* Support Vector Machines
* Association rules
* Scorecards (including reason codes)
* Ruleset Models (flat decision trees)
* Linear and Logistic regression as well as all general regression PMML models:
** Multinomial Logistic
** General Linear
** Ordinal Multinomial
** Simple Regression
** Generalized linear model
** Cox Regression Models
* Multiple Models: Model Composition, Ensembles, Segmentation, and Chaining.
as well as a variety of elements involved in data pre- and post-processing:
* Built-in Functions (logic and arithmetic operators as well as IF-THEN-ELSE)
* Normalization
* Discretization
* Value Mapping
* Custom Functions
* Targets/Scaling
* Outputs
* Model Verification (which in ADAPA can also take the form of a CSV file)
Once a model is uploaded in ADAPA, it can be executed in batch and real-time. ADAPA is a PMML consumer, therefore it is able to execute PMML code exported from tools such as R, SPSS, IBM, SAS, KNIME, KXEN, RapidMiner, etc.
Besides offering a web-based console to manage models and rule sets, ADAPA includes capabilities to test these under its decision and validation framework.
Business rules
Business rules allow for business process and logic to be expressed outside of programming code. In ADAPA, the integration of predictive analytics and rules is seamless. That is, predictive models can be embedded into rules. In this way, ADAPA allows both data-driven and expert knowledge to be combined into a single solution.
ADAPA allows for business knowledge to be expressed in tabular format. In ADAPA, rules can be used to manage the execution of different predictive models depending on the business context. They can also incorporate scores generated by different predictive models throughout the business process.
ADAPA rules leverage the power of the leading Java open-source rules engine Drools which is supported by a strong community of developers and JBoss, a division of Red Hat.
All decisions in ADAPA are readily available by the use of Web Services.
ADAPA To Go
PMML Converter
Zementis Inc (the maker of ADAPA) has released the PMML Converter tool. It allows for users to convert older PMML models (versions 2.0, 2.1, 3.0, 3.1, 3.2, 4.0) to version 4.1. Besides schema validation, the PMML Converter automatically corrects known issues with PMML code from several sources/vendors. The aim is to successfully validate code in older versions of PMML and convert them to PMML 4.1. Files in PMML 4.1 can also be passed through the converter so that they can be corrected and validated against the 4.1 schema.
The PMML Converter is also embedded in ADAPA itself. And so, if you use ADAPA, there is no need to convert your files, ADAPA will automatically do that for you.
Transformations Generator
PMML provides a variety of data transformations, including value mapping, normalization, and discretization. It also offers several built-in functions as well as arithmetic and logical operators which can be combined to represent complex pre-processing steps. With the Zementis Inc Transformations Generator tool, one can graphically design a transformation and obtain the respective PMML code. This can then be pasted into an existing PMML file and uploaded in ADAPA.
Software as a Service on the Cloud (Amazon EC2 and IBM SmartCloud)
ADAPA predictive analytics is available through the Amazon Elastic Compute Cloud (Amazon EC2) and the IBM SmartCloud (IBM cloud computing). It is the first SaaS (Software as a Service) predictive decisioning platform. The user can upload and manage several rule sets as well as models expressed in PMML and score data in real-time through the use of web-service calls (ADAPA will automatically convert older versions of PMML to version 4.1 and correct any known issues from different vendors). Since it is offered as a service in the cloud, ADAPA allows for users anywhere to deploy and execute state of the art data mining models.
ADAPA Add-in for Microsoft Office Excel
To simplify the process of executing predictive models, Zementis also offers the ADAPA add-in for Excel 2007 and 2010 (available for free). With the add-in, anyone in the enterprise is able to score data in Excel by executing models previously deployed in ADAPA.
ADAPA allows for real-time data scoring at any time a new event occurs since it can be used from inside any application via Web Service calls. Excel is just one such application which happens to be a very well known tool (used by many). The Excel Add-in frees users from having to deal with all the technology required for executing predictive models. With the Excel add-in, all one has to do is to select which data records to score (or the columns and rows containing the relevant data) and press on the “Score” button in Excel. When that is done, new predictions are generated automatically for all selected records.
ADAPA Flavors
ADAPA is currently being offered in three ways:
* On the Amazon Cloud: users can launch their own private instances of ADAPA on Amazon EC2.
* On the IBM SmartCloud: users can launch their own private instances of ADAPA on the IBM SmartCloud.
* On Site: ADAPA is also available for deployment on site or on a private cloud.
In-Database Scoring
Not all analytic tasks are born the same. If one is confronted with massive volumes of data that need to be scored on a regular basis, in-database scoring sounds like the logical thing to do. In all likelihood, the data in this case is already stored in a database and, with in-database scoring, there is no data movement. Data and models reside together hence scores and predictions flow on an accelerated pace.
Built on the heritage of the ADAPA Decision Engine, the Universal PMML Plug-in (UPPI) is a highly optimized, in-database scoring engine
for predictive models, fully supporting the PMML standard. With PMML, UPPI delivers a wide range of
predictive analytics for high performance scoring.
Scoring for Hadoop
Zementis and Datameer have partnered to deliver first-ever standards-based execution of predictive analytics on a massive parallel scale. This joint solution combines the Zementis Universal PMML Plug-in for real-time execution of predictive models with the power and scale of Datameer, an end-to-end BI solution that includes data source integration, an analytics engine, visualization and dashboarding.
The Universal PMML Plug-in for Datameer brings together essential technologies, offering the best combination of open standards and scalability for the application of predictive analytics. The Plug-in fully supports the Predictive Model Markup Language (PMML), the de facto standard for data mining applications, which enables the integration of predictive models from IBM/SPSS, SAS, R, and many more.

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