Tag: open

September Roundup by Revolution

From the monthly newsletter- which I consider quite useful for keeping updated on application of R

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Revolution News
Every month, we’ll bring you the latest news about Revolution’s products and events in this section. Follow us on Twitter at @RevolutionR for up-to-the-minute news and updates from Revolution Analytics!

Revolution R Enterprise 4.0 for Windows now available. Based on the latest R 2.11.1 and including the RevoScaleR package for big-data analysis in R, Revolution R Enterprise is now available for download for Windows 32-bit and 64-bit systems. Click here to subscribe, or available free to academia.

New! Integrate R with web applications, BI dashboards and more with web services. RevoDeployR is a new Web Services framework that integrates dynamic R-based computations into applications for business users. It will be available September 30 with Revolution R Enterprise Server on RHEL 5. Click here to learn more.

Free Webinar, September 22: In a joint webinar from Revolution Analytics and Jaspersoft, learn how to use RevoDeployR to integrate advanced analytics on-demand in applications, BI dashboards, and on the web. Register here.

Revolution in the News: SearchBusinessAnalytics.com previews the forthcoming Revolution R GUI; Channel Register introduces RevoDeployR, while IT Business Edge shows off the Web Services architecture; and ReadWriteWeb.com looks at how RevoScaleR tackles the Big Data explosion.

Inside-R: A new site for the R Community. At www.inside-R.org you’ll find the latest information about R from around the Web, searchable R documentation and packages, hints and tips about R, and more. You can even add a “Download R” badge to your own web-page to help spread the word about R.

R News, Tips and Tricks from the Revolutions blog
The Revolutions blog brings you daily news and tips about R, statistics and open source. Here are some highlights from Revolutions from the past month.

R’s key role in the oil spill response: Read how NIST’s Division Chief of Statistical Engineering used R to provide critical analysis in real time to the Secretaries of Energy and the Interior, and helped coordinate the government’s response.

Animating data with R and Google Earth: Learn how to use R to create animated visualizations of geographical data with Google Earth, such as this video showing how tuna migrations intersect with the location of the Gulf oil spill.

Are baseball games getting longer? Or is it just Red Sox games? Ryan Elmore uses nonparametric regression in R to find out.

Keynote presentations from useR! 2010: the worldwide R user’s conference was a great success, and there’s a wealth of useful tips and information in the presentations. Video of the keynote presentations are available too: check out in particular Frank Harrell’s talk Information Allergy, and Friedrich Leisch’s talk on reproducible statistical research.

Looking for more R tips and tricks? Check out the monthly round-ups at the Revolutions blog.

Upcoming Events
Every month, we’ll highlight some upcoming events from R Community Calendar.

September 23: The San Diego R User Group has a meetup on BioConductor and microarray data analysis.

September 28: The Sydney Users of R Forum has a meetup on building world-class predictive models in R (with dinner to follow).

September 28: The Los Angeles R User Group presents an introduction to statistical finance with R.

September 28: The Seattle R User Group meets to discuss, “What are you doing with R?”

September 29: The Raleigh-Durham-Chapel Hill R Users Group has its first meeting.

October 7: The NYC R User Group features a presentation by Prof. Andrew Gelman.

There are also new R user groups in Singapore, Seoul, Denver, Brisbane, and New Jersey.  Please let us know if we’re missing your R user group, or if want to get a new one started.

———————————————————————————————-Editor

David Smith, VP Marketing
david@revolutionanalytics.com
Twitter: @revodavid

subscribe here for Revo’s Monthly newsletter-

Making NeW R

Tal G in his excellent blog piece talks of “Why R Developers  should not be paid” http://www.r-statistics.com/2010/09/open-source-and-money-why-r-developers-shouldnt-be-paid/

His argument of love is not very original though it was first made by these four guys

I am going to argue that “some” R developers should be paid, while the main focus should be volunteers code. These R developers should be paid as per usage of their packages.

Let me expand.

Imagine the following conversation between Ross Ihaka, Norman Nie and Peter Dalgaard.

Norman- Hey Guys, Can you give me some code- I got this new startup.

Ross Ihaka and Peter Dalgaard- Sure dude. Here is 100,000 lines of code, 2000 packages and 2 decades of effort.

Norman- Thanks guys.

Ross Ihaka- Hey, What you gonna do with this code.

Norman- I will better it. Sell it. Finally beat Jim Goodnight and his **** Proc GLM and **** Proc Reg.

Ross- Okay, but what will you give us? Will you give us some code back of what you improve?

Norman – Uh, let me explain this open core …

Peter D- Well how about some royalty?

Norman- Sure, we will throw parties at all conferences, snacks you know at user groups.

Ross – Hmm. That does not sound fair. (walks away in a huff muttering)-He takes our code, sells it and wont share the code

Peter D- Doesnt sound fair. I am back to reading Hamlet, the great Dane, and writing the next edition of my book. I am glad I wrote a book- Ross didnt even write that.

Norman-Uh Oh. (picks his phone)- Hey David Smith, We need to write some blog articles pronto – these open source guys ,man…

———–I think that sums what has been going on in the dynamics of R recently. If Ross Ihaka and R Gentleman had adopted an open core strategy- meaning you can create packages to R but not share the original where would we all be?

At this point if he is reading this, David Smith , long suffering veteran of open source  flameouts is rolling his eyes while Tal G is wondering if he will publish this on R Bloggers and if so when or something.

Lets bring in another R veteran-  Hadley Wickham who wrote a book on R and also created ggplot. Thats the best quality, most often used graphics package.

In terms of economic utilty to end user- the ggplot package may be as useful if not more as the foreach package developed by Revolution Computing/Analytics.

Now http://cran.r-project.org/web/packages/foreach/index.html says that foreach is licensed under http://www.apache.org/licenses/LICENSE-2.0

However lets come to open core licensing ( read it here http://alampitt.typepad.com/lampitt_or_leave_it/2008/08/open-core-licen.html ) which is where the debate is- Revolution takes code- enhances it (in my opinion) substantially with new formats XDF for better efficieny, web services API, and soon coming next year a GUI (thanks in advance , Dr Nie and guys)

and sells this advanced R code to businesses happy to pay ( they are currently paying much more to DR Goodnight and HIS guys)

Why would any sane customer buy it from Revolution- if he could download exactly the same thing from http://r-project.org

Hence the business need for Revolution Analytics to have an enhanced R- as they are using a product based software model not software as a service model.

If Revolution gives away source code of these new enhanced codes to R core team- how will R core team protect the above mentioned intelectual property- given they have 2 decades experience of giving away free code , and back and forth on just code.

Now Revolution also has a marketing budget- and thats how they sponsor some R Core events, conferences, after conference snacks.

How would people decide if they are being too generous or too stingy in their contribution (compared to the formidable generosity of SAS Institute to its employees, stakeholders and even third party analysts).

Would it not be better- IF Revolution can shift that aspect of relationship to its Research and Development budget than it’s marketing budget- come with some sort of incentive for “SOME” developers – even researchers need grants and assistantships, scholarships, make a transparent royalty formula say 17.5 % of the NEW R sales goes to R PACKAGE Developers pool, which in turn examines usage rate of packages and need/merit before allocation- that would require Revolution to evolve from a startup to a more sophisticated corporate and R Core can use this the same way as John M Chambers software award/scholarship

Dont pay all developers- it would be an insult to many of them – say Prof Harrell creator of HMisc to accept – but can Revolution expand its dev base (and prospect for future employees) by even sponsoring some R Scholarships.

And I am sure that if Revolution opens up some more code to the community- they would the rest of the world and it’s help useful. If it cant trust people like R Gentleman with some source code – well he is a board member.

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Now to sum up some technical discussions on NeW R

1)  An accepted way of benchmarking efficiencies.

2) Code review and incorporation of efficiencies.

3) Multi threading- Multi core usage are trends to be incorporated.

4) GUIs like R Commander E Plugins for other packages, and Rattle for Data Mining to have focussed (or Deducer). This may involve hiring User Interface Designers (like from Apple 😉  who will work for love AND money ( Even the Beatles charge royalty for that song)

5) More support to cloud computing initiatives like Biocep and Elastic R – or Amazon AMI for using cloud computers- note efficiency arguements dont matter if you just use a Chrome Browser and pay 2 cents a hour for an Amazon Instance. Probably R core needs more direct involvement of Google (Cloud OS makers) and Amazon as well as even Salesforce.com (for creating Force.com Apps). Note even more corporates here need to be involved as cloud computing doesnot have any free and open source infrastructure (YET)

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Debates will come and go. This is an interesting intellectual debate and someday the liitle guys will win the Revolution-

From Hugh M of Gaping Void-

http://www.gapingvoid.com/Moveable_Type/archives/cat_microsoft_blue_monster_series.html

HOW DOES A SOFTWARE COMPANY MAKE MONEY, IF ALL

SOFTWARE IS FREE?

“If something goes wrong with Microsoft, I can phone Microsoft up and have it fixed. With Open Source, I have to rely on the community.”

And the community, as much as we may love it, is unpredictable. It might care about your problem and want to fix it, then again, it may not. Anyone who has ever witnessed something online go “viral”, good or bad, will know what I’m talking about.

and especially-

http://gapingvoid.com/2007/04/16/how-well-does-open-source-currently-meet-the-needs-of-shareholders-and-ceos/

Source-http://gapingvoidgallery.com/

Kind of sums up why the open core licensing is all about.

Oracle Open World/ RODM package

From the press release, here comes Oracle Open World. They really have an excellent rock concert in that as well.

.NET and Windows @ Oracle Develop and Oracle OpenWorld 2010

Oracle Develop will again feature a .NET track for Oracle developers. Oracle Develop is suited for all levels of .NET developers, from beginner to advanced. It covers introductory Oracle .NET material, new features, deep dive application tuning, and includes three hours of hands-on labs apply what you learned from the sessions.

To register, go to Oracle Develop registration site.

Oracle OpenWorld will include several sessions on using the Oracle Database on Windows and .NET.

Session schedules and locations for Windows and .NET sessions at Oracle Develop and OpenWorld are now available.

Download: 32-bit ODAC 11.2.0.1.2 for Visual Studio 2010 and .NET Framework 4

With ODAC 11.2.0.1.2, developers can connect to Oracle Database versions 9.2 and higher from Visual Studio 2010 and .NET Framework 4. ODAC components support the full framework, as well as the new .NET Framework Client Profile.

Statement of Direction: Oracle Database and Microsoft Entity Framework

Learn about Oracle’s beta and production plans to support Microsoft Entity Framework with Oracle Database.

Also see http://www.oracle.com/technetwork/articles/datawarehouse/saternos-r-161569.html

for

Data Mining Using the RDOM Package

By Casimir Saternos

Some excerpts-

Open R and enter the following command.

> library(RODM)

This command loads the RODM library and as well the dependent RODBC package. The next step is to make a database connection.

> DB <- RODM_open_dbms_connection(dsn="orcl", uid="dm", pwd="dm")

Subsequent commands use the DB object (an instance of the RODBC class) to connect to the database. The DNS specified in the command is the name you used earlier for the Data Source Name during the ODBC connection configuration. You can view the actual R code being executed by the command by simply typing the function name (without parentheses).

> RODM_open_dbms_connection

And say making a Model in Oracle and R-

> numrows <- length(orange_data[,1])
> orange_data.rows <- length(orange_data[,1])
> orange_data.id <- matrix(seq(1, orange_data.rows),  nrow=orange_data.rows, ncol=1, dimnames= list(NULL, c(“CASE_ID”)))
> orange_data <- cbind(orange_data.id, orange_data)

This adjustment to the data frame then needs to be propagated to the database. You can confirm the change using the sqlColumns function, as listed earlier.

> RODM_create_dbms_table(DB, "orange_data")
> sqlColumns(DB, 'orange_data')$COLUMN_NAME

> glm <- RODM_create_glm_model(
database = DB,
data_table_name = “orange_data”,
case_id_column_name = “CASE_ID”,
target_column_name = “circumference”,
model_name = “GLM_MODEL”,
mining_function = “regression”)

Information about this model can then be obtained by analyzing value returned from the model and stored in the variable named glm.

> glm$model.model_settings
> glm$glm.globals
> $glm.coefficients

Once you have a model, you can apply the model to a new set of data. To begin, create or retrieve sample data in the same format as the training data.

> query<-('select 999 case_id, 1 tree, 120 age, 
32 circumference from dual')

> orange_test<-sqlQuery(DB, query)
> RODM_create_dbms_table(DB, "orange_test")
and 
Finally, the model can be applied to the new data set and the results analyzed.


results <- RODM_apply_model(database = DB, 
data_table_name = "orange_test",
model_name = "GLM_MODEL",
supplemental_cols = "circumference")

When your session is complete, you can clean up objects that were created (if you like) and you should close the database connection:

> RODM_drop_model(database=DB,'GLM_MODEL')
> RODM_drop_dbms_table(DB, "orange_test")
> RODM_drop_dbms_table(DB, "orange_data")
> RODM_close_dbms_connection(DB)

See the full article at http://www.oracle.com/technetwork/articles/datawarehouse/saternos-r-161569.html

Kill R? Wait a sec

1) Is R efficient? (scripting wise, and performance wise) _ Depends on how you code it- some Packages like foreach can help but basic efficiency come from programmer. XDF formats from Revoscalar -the non open R package further improve programming efficiency

2) Should R be written from scratch?

You got to be kidding- It depends on how you define scratch after 2 million users

This has been done with S, then S Plus and now R.

3) What should be the license of R (if it was made a new)?

GPL license is fine. You need to do a better job of executing the license. Currently interfaces to R exist from SPSS, SAS, KXEN , other companies as well. To my knowledge royalty payments as well as formal code sharing does not agree.

R core needs to do a better job of protecting the work of 2500 package-creators rather than settling for a few snacks at events, sponsorships, Corporate Board Membership for Prof Gentleman, and 4-5 packages donated to it. The only way R developers can currently support their research is write a book (ny Springer mostly)

Eg GGplot and Hmisc are likely to be used more by average corporate user. Do their creators deserve royalty if creators of RevoScalar are getting it?

If some of 2 million users gave 1 $ to R core (compared to 9 million in last round of funding in Revolution Analytics)- you would have enough money to create a 64 bit optimized R for Linux (missing in Enterprise R), Amazon R APIs (like Karim Chine’s efforts), R GUIs (like Rattle’s commercial version) etc etc

The developments are not surprising given that Microsoft and Intel are funding Revolution Analytics http://www.dudeofdata.com/?p=1967

R controversies come and go (this has happened before including the NYT article and shakeup at Revo)

An interesting debate on whether R should be killed to make an upgrade to a more efficient language.

From Tal (creator R Bloggers) and on R help list-

There is currently a (very !) lively discussions happening around the web, surrounding the following topics:
1) Is R efficient? (scripting wise, and performance wise)
2) Should R be written from scratch?
3) What should be the license of R (if it was made a new)?

Very serious people have taken part in the debates so far.  I hope to let you know of the places I came by, so you might be able to follow/participate
in these (IMHO) important discussions.

The discussions started in the response for the following blog post on
Xi’An’s blog:
http://xianblog.wordpress.com/2010/09/06/insane/


Followed by the (short) response post by Ross Ihaka:
http://xianblog.wordpress.com/2010/09/13/simply-start-over-and-build-something-better/


Other discussions started to appear on Andrew Gelman’s blog:
http://www.stat.columbia.edu/~cook/movabletype/archives/2010/09/ross_ihaka_to_r.html

And (many) more responses started to appear in the hackers news website:
http://news.ycombinator.com/item?id=1687054

I hope these discussions will have fruitful results for our community,
Tal

—————-Contact
Details:——————————————————-
Contact me: Tal.Galili@gmail.com |  972-52-7275845
Read me: www.talgalili.com (Hebrew) | www.biostatistics.co.il (Hebrew) |
www.r-statistics.com (English)

My 0 cents ( see it would 2 cents but it;s free)

Trrrouble in land of R…and Open Source Suggestions

Recently some comments by Ross Ihake , founder of R Statistical Software on Revolution Analytics, leading commercial vendor of R….. came to my attention-

http://www.stat.auckland.ac.nz/mail/archive/r-downunder/2010-May/000529.html

[R-downunder] Article on Revolution Analytics

Ross Ihaka ihaka at stat.auckland.ac.nz
Mon May 10 14:27:42 NZST 2010

On 09/05/10 09:52, Murray Jorgensen wrote:
> Perhaps of interest:
>
> http://www.theregister.co.uk/2010/05/06/revolution_commercial_r/

Please note that R is "free software" not "open source".  These guys
are selling a GPLed work without disclosing the source to their part
of the work. I have complained to them and so far they have given me
the brush off. I am now considering my options.

Don't support these guys by buying their product. The are not feeding
back to the rights holders (the University of Auckland and I are rights
holders and they didn't even have the courtesy to contact us).

--
Ross Ihaka                         Email:  ihaka at stat.auckland.ac.nz
Department of Statistics           Phone:  (64-9) 373-7599 x 85054
University of Auckland             Fax:    (64-9) 373-7018
Private Bag 92019, Auckland
New Zealand
and from http://www.theregister.co.uk/2010/05/06/revolution_commercial_r/
Open source purists probably won't be all too happy to learn that Revolution is going to be employing an "open core" strategy, which means the core R programs will remain open source and be given tech support under a license model, but the key add-ons that make R more scalable will be closed source and sold under a separate license fee. Because most of those 2,500 add-ons for R were built by academics and Revolution wants to supplant SPSS and SAS as the tools used by students, Revolution will be giving the full single-user version of the R Enterprise stack away for free to academics. 
Conclusion-
So one co-founder of R is advocating not to buy from Revolution Analytics , which has the other co-founder of R, Gentleman on its board. 
Source- http://www.revolutionanalytics.com/aboutus/leadership.php

2) If Revolution Analytics is using 2500 packages for free but insisting on getting paid AND closing source of it’s packages (which is a technical point- how exactly can you prevent source code of a R package from being seen)

Maybe there can be a PACKAGE marketplace just like Android Apps, Facebook Apps, and Salesforce.com Apps – so atleast some of the thousands of R package developers can earn – sorry but email lists do not pay mortgages and no one is disputing the NEED for commercializing R or rewarding developers.

Though Barr created SAS, he gave up control to Goodnight and Sall https://decisionstats.wordpress.com/2010/06/02/sas-early-days/

and Goodnight and Sall do pay their developers well- to the envy of not so well paid counterparts.

3) I really liked the innovation of Revolution Analytics RevoScalar, and I wish that the default R dataset be converted to XDF dataset so that it basically kills

off the R criticism of being slow on bigger datasets. But I also realize the need for creating an analytics marketplace for R developers and R students- so academic version of R being free and Revolution R being paid seems like a trade off.

Note- You can still get a job faster as a stats student if you mention SAS and not R as a statistical skill- not all stats students go into academics.

4) There can be more elegant ways of handling this than calling for ignoring each other as REVOLUTION and Ihake seem to be doing to each other.

I can almost hear people in Cary, NC chuckling at Norman Nie, long time SPSS opponent and now REVOLUTION CEO, and his antagonizing R’s academicians within 1 year of taking over- so I hope this ends well for all. The road to hell is paved with good intentions- so if REVOLUTION can share some source code with say R Core members (even Microsoft shares source code with partners)- and R Core and Revolution agree on a licensing royalty from each other, they can actually speed up R package creation rather than allow this 2 decade effort to end up like S and S plus and TIBCO did.

Maybe Richard Stallman can help-or maybe Ihaka has a better sense of where things will go down in a couple of years-he must know something-he invented it, didnt he

On 09/05/10 09:52, Murray Jorgensen wrote:
> Perhaps of interest:
>
> http://www.theregister.co.uk/2010/05/06/revolution_commercial_r/

Please note that R is "free software" not "open source".  These guys
are selling a GPLed work without disclosing the source to their part
of the work. I have complained to them and so far they have given me
the brush off. I am now considering my options.

Don't support these guys by buying their product. The are not feeding
back to the rights holders (the University of Auckland and I are rights
holders and they didn't even have the courtesy to contact us).

--
Ross Ihaka                         Email:  ihaka at stat.auckland.ac.nz
Department of Statistics           Phone:  (64-9) 373-7599 x 85054
University of Auckland             Fax:    (64-9) 373-7018
Private Bag 92019, Auckland
New Zealand

Open Source Business Intelligence: Pentaho and Jaspersoft

Here are two products that are used widely for Business Intelligence_ They are open source and both have free preview.

Jaspersoft-For the Enterprise version click on the screenshot while for the free community version you can go to

http://jasperforge.org/projects/jasperserver

Interestingly (and not surprisingly) Revolution Analytics is teaming up with Jaspersoft to use R for reporting along with the Jaspersoft BI stack.

ADVANCED ANALYTICS ON DEMAND IN APPLICATIONS, IN DASHBOARDS, AND ON THE WEB

FREE WEBINAR WEDNESDAY, SEPTEMBER 22ND @9AM PACIFIC

DEPLOYING R: ADVANCED ANALYTICS ON DEMAND IN APPLICATIONS, IN DASHBOARDS, AND ON THE WEB

A JOINT WEBINAR FROM REVOLUTION ANALYTICS AND JASPERSOFT

Date: Wednesday, September 22, 2010
Time: 9:00am PDT (12:00pm EDT; 4:00pm GMT)
Presenters: David Smith, Vice President of Marketing, Revolution Analytics
Andrew Lampitt, Senior Director of Technology Alliances, Jaspersoft
Matthew Dahlman, Business Development Engineer, Jaspersoft
Registration: Click here to register now!

R is a popular and powerful system for creating custom data analysis, statistical models, and data visualizations. But how can you make the results of these R-based computations easily accessible to others? A PhD statistician could use R directly to run the forecasting model on the latest sales data, and email a report on request, but then the process is just going to have to be repeated again next month, even if the model hasn’t changed. Wouldn’t it be better to empower the Sales manager to run the model on demand from within the BI application she already uses—daily, even!—and free up the statistician to build newer, better models for others?

In this webinar, David Smith (VP of Marketing, Revolution Analytics) will introduce the new “RevoDeployR” Web Services framework for Revolution R Enterprise, which is designed to make it easy to integrate dynamic R-based computations into applications for business users. RevoDeployR empowers data analysts working in R to publish R scripts to a server-based installation of Revolution R Enterprise. Application developers can then use the RevoDeployR Web Services API to securely and scalably integrate the results of these scripts into any application, without needing to learn the R language. With RevoDeployR, authorized users of hosted or cloud-based interactive Web applications, desktop applications such as Microsoft Excel, and BI applications like Jaspersoft can all benefit from on-demand analytics and visualizations developed by expert R users.

To demonstrate the power of deploying R-based computations to business users, Andrew Lampitt will introduce Jaspersoft commercial open source business intelligence, the world’s most widely used BI software. In a live demonstration, Matt Dahlman will show how to supercharge the BI process by combining Jaspersoft and Revolution R Enterprise, giving business users on-demand access to advanced forecasts and visualizations developed by expert analysts.

Click here to register for the webinar.

Speaker Biographies:

David Smith is the Vice President of Marketing at Revolution Analytics, the leading commercial provider of software and support for the open source “R” statistical computing language. David is the co-author (with Bill Venables) of the official R manual An Introduction to R. He is also the editor of Revolutions (http://blog.revolutionanalytics.com), the leading blog focused on “R” language, and one of the originating developers of ESS: Emacs Speaks Statistics. You can follow David on Twitter as @revodavid.

Andrew Lampitt is Senior Director of Technology Alliances at Jaspersoft. Andrew is responsible for strategic initiatives and partnerships including cloud business intelligence, advanced analytics, and analytic databases. Prior to Jaspersoft, Andrew held other business positions with Sunopsis (Oracle), Business Objects (SAP), and Sybase (SAP). Andrew earned a BS in engineering from the University of Illinois at Urbana Champaign.

Matthew Dahlman is Jaspersoft’s Business Development Engineer, responsible for technical aspects of technology alliances and regional business development. Matt has held a wide range of technical positions including quality assurance, pre-sales, and technical evangelism with enterprise software companies including Sybase, Netonomy (Comverse), and Sunopsis (Oracle). Matt earned a BA in mathematics from Carleton College in Northfield, Minnesota.


The second widely used BI stack in open source is Pentaho.

You can download it here to evaluate it or click on screenshot to read more at

http://community.pentaho.com/

http://sourceforge.net/projects/pentaho/files/Business%20Intelligence%20Server/

Event: Predictive analytics with R, PMML and ADAPA

From http://www.meetup.com/R-Users/calendar/14405407/

The September meeting is at the Oracle campus. (This is next door to the Oracle towers, so there is plenty of free parking.) The featured talk is from Alex Guazzelli (Vice President – Analytics, Zementis Inc.) who will talk about “Predictive analytics with R, PMML and ADAPA”.

Agenda:
* 6:15 – 7:00 Networking and Pizza (with thanks to Revolution Analytics)
* 7:00 – 8:00 Talk: Predictive analytics with R, PMML and ADAPA
* 8:00 – 8:30 General discussion

Talk overview:

The rule in the past was that whenever a model was built in a particular development environment, it remained in that environment forever, unless it was manually recoded to work somewhere else. This rule has been shattered with the advent of PMML (Predictive Modeling Markup Language). By providing a uniform standard to represent predictive models, PMML allows for the exchange of predictive solutions between different applications and various vendors.

Once exported as PMML files, models are readily available for deployment into an execution engine for scoring or classification. ADAPA is one example of such an engine. It takes in models expressed in PMML and transforms them into web-services. Models can be executed either remotely by using web-services calls, or via a web console. Users can also use an Excel add-in to score data from inside Excel using models built in R.

R models have been exported into PMML and uploaded in ADAPA for many different purposes. Use cases where clients have used the flexibility of R to develop and the PMML standard combined with ADAPA to deploy range from financial applications (e.g., risk, compliance, fraud) to energy applications for the smart grid. The ability to easily transition solutions developed in R to the operational IT production environment helps eliminate the traditional limitations of R, e.g. performance for high volume or real-time transactional systems and memory constraints associated with large data sets.

Speaker Bio:

Dr. Alex Guazzelli has co-authored the first book on PMML, the Predictive Model Markup Language which is the de facto standard used to represent predictive models. The book, entitled PMML in Action: Unleashing the Power of Open Standards for Data Mining and Predictive Analytics, is available on Amazon.com. As the Vice President of Analytics at Zementis, Inc., Dr. Guazzelli is responsible for developing core technology and analytical solutions under ADAPA, a PMML-based predictive decisioning platform that combines predictive analytics and business rules. ADAPA is the first system of its kind to be offered as a service on the cloud.
Prior to joining Zementis, Dr. Guazzelli was involved in not only building but also deploying predictive solutions for large financial and telecommunication institutions around the globe. In academia, Dr. Guazzelli worked with data mining, neural networks, expert systems and brain theory. His work in brain theory and computational neuroscience has appeared in many peer reviewed publications. At Zementis, Dr. Guazzelli and his team have been involved in a myriad of modeling projects for financial, health-care, gaming, chemical, and manufacturing industries.

Dr. Guazzelli holds a Ph.D. in Computer Science from the University of Southern California and a M.S and B.S. in Computer Science from the Federal University of Rio Grande do Sul, Brazil.