Wednesday, May 21, 2008

What is an ADAPA instance?

For the definition of an ADAPA instance on the Amazon Cloud, click HERE.

Tuesday, May 20, 2008

What is the scoop behind PMML and Amazon EC2?

Organizations increasingly recognize the value that predictive analytics offers to their business. The complexity of development, integration, and deployment of predictive models, however, is often considered cost-prohibitive for many projects. In light of mature open source solutions, open standards, and SOA principles we propose an agile model development life cycle that allows us to quickly leverage predictive analytics in operational environments.

Starting with data analysis and model development, you can effectively use the Predictive Model Markup Language (PMML) standard, to move complex decision models from the scientist's desktop into a scalable production environment hosted on the Amazon Elastic Compute Cloud (Amazon EC2).

Expressing Models in PMML

PMML is an XML-based language used to define predictive models. It was specified by the Data Mining Group, an independent group of leading technology companies including Zementis. By providing a uniform standard to represent such models, PMML allows for the exchange of predictive solutions between different applications and various vendors.

Open source statistical tools such as R can be used to develop data mining models based on historical data. R allows for models to be exported into PMML which can then be imported into an operational decision platform and be ready for production use in a matter of minutes.

On-Demand Predictive Analytics

Amazon EC2 is a reliable, on-demand infrastructure on which we offer the ADAPA® (Adaptive Decision And Predictive Analytics) Predictive Decisioning Engine based on the Software as a Service (SaaS) paradigm. ADAPA imports models expressed in PMML and executes these in batch mode, or real-time via web-services.

Our service is implemented as a private, dedicated Amazon EC2 instance of ADAPA. Each client has access to his/her own ADAPA Engine instance via HTTP/HTTPS. In this way, models and data for one client never share the same engine with other clients.

The ADAPA Control Center

In order to have ADAPA readily available on Amazon EC2, we built the ADAPA Control Center application which allows for the user launch and manage all ADAPA instances from a single location (see figure below).

Our service easily scales together with the client’s organizational needs for more power and predictive analytics resources. From the ADAPA Control Center, one can launch new as well as terminate existing instances. Amazon EC2 offers five different instances’ types to address different processing needs. These are: small, large, extra-large, and high-CPU (medium and extra-large) as well as high-memory (extra-large, double extra-large, and quadruple extra-large). Also, whenever an instance is no longer necessary, it can be terminated in a matter of seconds.

The ADAPA Console

Each instance executes a single version of the ADAPA engine, which can be easily accessed through the Control Center. The engine itself is accessible through the ADAPA Console which allows for the easy managing of predictive models and data files. The instance owner can use the console to upload new models as well as score or classify records on data files in batch mode. Real-time execution of models is achieved through the use of web-services. The ADAPA Console offers a very intuitive interface which is divided into two main sections: model and data management. These allow for existing models to be used for generating decisions on different data sets. Also, new models can be easily uploaded and existing models can be removed in a matter of seconds.

Using a SaaS solution to break down traditional barriers that currently slow the adoption of predictive analytics, our strategy translates predictive models into operational assets with minimal deployment costs and leverages the inherent scalability of utility computing.

In summary, ADAPA revolutionizes the world of predictive analytics, since it allows for:

  • Cost-effective and reliable service based on Amazon’s EC2 infrastructure

  • Secure execution of predictive models through dedicated and controlled instances including HTTPS and Web-Services security

  • On-demand computing. Choice of instance type (small, large, and extra-large) and launch of multiple instances.

  • Superior time-to-market by providing rapid deployment of predictive models and an agile enterprise decision management environment.

Friday, May 9, 2008

How does ADAPA handle missing values for Decision Trees?

PMML offers many different strategies for the handling of missing values in Decision Trees. ADAPA supports all of them. These are:

  • lastPrediction

  • nullPrediction

  • defaultChild

  • weightedConfidence

  • aggregateNodes

  • none (default strategy)

For information on each strategy, please visit, for example, the PMML 3.2 Decision Trees specification page at the Data Mining Group website.

Thursday, May 8, 2008

How can I use the ADAPA Control Center?

This posting has been moved to the Zementis Support Site. You can still access it by clicking HERE.

How can I use the ADAPA Console?

This posting has been moved to the Zementis Support Site. You can still access it by clicking HERE.

What are the benefits of running ADAPA on Amazon EC2?

ADAPA can be used in different ways for a variety of decisioning solutions. Whereas ADAPA on Site can be deployed on-site through a server install or on your private cloud, ADAPA on the Cloud is being offered as a service through the Amazon Elastic Compute Cloud (Amazon EC2).

Amazon EC2 is a web service that provides resizable compute capacity in the Cloud. It is designed to make web-scale computing easier. Amazon EC2 provides you with complete control of your computing resources and lets you run on Amazon's proven computing environment.

By utilizing the ADAPA Control Center, you can launch and terminate a new ADAPA instance in minutes which allows you to quickly scale capacity, both up and down, as your computing requirements change.

Finally, by offering ADAPA on Amazon EC2 as a service changes the economics of predictive analytics by allowing you to pay only for computing that you actually use. What a concept ... huh?

What is the ADAPA Console and how can I access it?

This posting has been moved to the Zementis Support Site. You can still access it by clicking HERE.

Does ADAPA support decision trees?

Yes, decision trees are part of the modeling elements supported by ADAPA (to see a list of all techniques click here).

You can build your decision tree model with different training algorithms, export the tree as a PMML file (or convert the resulting model to PMML), and upload it into ADAPA for decisioning.

Does ADAPA support all modeling techniques specified in PMML?

We are constantly working towards that goal. Currently, ADAPA supports several PMML elements, including pre- and post-processing elements.

As for modeling techniques it currently supports the following PMML elements:
  • Neural Networks
  • Support Vector Machines
  • Association Rules
  • Regression
  • General Regression
  • Decision Trees
  • Clustering Models
  • Naive Bayes Classifiers
  • Ruleset Models
  • Multiple models (ensembles, segmentation, and model composition)
If you are interested in using ADAPA but the PMML element you use is not listed in here, feel free to contact us.

If you are unsure about what a PMML element represents, please check the DMG (Data Mining Group) webpage which defines PMML . Also, take a look at the feature list for the ADAPA Predictive Analytics Engine for a full feature list of all the PMML elements supported.

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