Scoring SAS and SPSS Models in the cloud

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An announcement from Zementis and Predixion Software– about using cloud computing for scoring models using PMML. Note R has a PMML package as well which is used by Rattle, data mining GUI for exporting models.

Source- http://www.marketwatch.com/story/predixion-software-introduces-new-product-to-run-sas-and-spss-predictive-models-in-the-cloud-2010-10-19?reflink=MW_news_stmp

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ALISO VIEJO, Calif., Oct 19, 2010 (BUSINESS WIRE) — Predixion Software today introduced Predixion PMML Connexion(TM), an interface that provides Predixion Insight(TM), the company’s low-cost, self-service in the cloud predictive analytics solution, direct and seamless access to SAS, SPSS (IBM) and other predictive models for use by Predixion Insight customers. Predixion PMML Connexion enables companies to leverage their significant investments in legacy predictive analytics solutions at a fraction of the cost of conventional licensing and maintenance fees.

The announcement was made at the Predictive Analytics World conference in Washington, D.C. where Predixion also announced a strategic partnership with Zementis, Inc., a market leader in PMML-based solutions. Zementis is exhibiting in Booth #P2.

The Predictive Model Markup Language (PMML) standard allows for true interoperability, offering a mature standard for moving predictive models seamlessly between platforms. Predixion has fully integrated this PMML functionality into Predixion Insight, meaning Predixion Insight users can now effortlessly import PMML-based predictive models, enabling information workers to score the models in the cloud from anywhere and publish reports using Microsoft Excel(R) and SharePoint(R). In addition, models can also be written back into SAS, SPSS and other platforms for a truly collaborative, interoperable solution.

“Predixion’s investment in this PMML interface makes perfect business sense as the lion’s share of the models in existence today are created by the SAS and SPSS platforms, creating compelling opportunity to leverage existing investments in predictive and statistical models on a low-cost cloud predictive analytics platform that can be fed with enterprise, line of business and cloud-based data,” said Mike Ferguson, CEO of Intelligent Business Strategies, a leading analyst and consulting firm specializing in the areas of business intelligence and enterprise business integration. “In this economy, Predixion’s low-cost, self-service predictive analytics solutions might be welcome relief to IT organizations chartered with quickly adding additional applications while at the same time cutting costs and staffing.”

“We are pleased to be partnering with Zementis, truly a PMML market leader and innovator,” said Predixion CEO Simon Arkell. “To allow any SAS or SPSS customer to immediately score any of their predictive models in the cloud from within Predixion Insight, compare those models to those created by Predixion Insight, and share the results within Excel and Sharepoint is an exciting step forward for the industry. SAS and SPSS customers are fed up with the high prices they must pay for their business users just to access reports generated by highly skilled PhDs who are burdened by performing routine tasks and thus have become a massive bottleneck. That frustration is now a thing of the past because any information worker can now unlock the power of predictive analytics without relying on experts — for a fraction of the cost and from anywhere they can connect to the cloud,” Arkell said.

Dr. Michael Zeller, Zementis CEO, added, “Our mission is to significantly shorten the time-to-market for predictive models in any industry. We are excited to be contributing to Predixion’s self-service, cloud-based predictive analytics solution set.”

About Predixion Software

Predixion Software develops and markets collaborative predictive analytics solutions in the public and private cloud. Predixion enables self-service predictive analytics, allowing customers to use and analyze large amounts of data to make actionable decisions, all within the familiar environment of Excel and PowerPivot. Predixion customers are achieving immediate results across a multitude of industries including: retail, finance, healthcare, marketing, telecommunications and insurance/risk management.

Predixion Software is headquartered in Aliso Viejo, California with development offices in Redmond, Washington. The company has venture capital backing from established investors including DFJ Frontier, Miramar Venture Partners and Palomar Ventures. For more information please contact us at 949-330-6540, or visit us atwww.predixionsoftware.com.

About Zementis

Zementis, Inc. is a leading software company focused on the operational deployment and integration of predictive analytics and data mining solutions. Its ADAPA(R) decision engine successfully bridges the gap between science and engineering. ADAPA(R) was designed from the ground up to benefit from open standards and to significantly shorten the time-to-market for predictive models in any industry. For more information, please visit www.zementis.com.

 

So which software is the best analytical software? Sigh- It depends

 

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Here is the software matrix that I am trying to develop for analytical software- It should help as a tentative guide for software purchases- it’s independent so unbiased (hopefully)- and it will try and bring as much range or sensitivity as possible. The list (rather than matrix) is of the format-

Type 0f analysis-

  • Data Visualization (Reporting with Pivot Ability to aggregate, disaggregate)
  • Reporting without Pivot Ability
  • Regression -Logistic Regression for Propensity or Risk Models
  • Regression- Linear for Pricing Models
  • Hypothesis Testing
  • A/B Scenario Testing
  • Decision Trees (CART, CHAID)
  • Time Series Forecasting
  • Association Analysis
  • Factor Analysis
  • Survey (Questionnaires)
  • Clustering
  • Segmentation
  • Data Manipulation

Dataset Size-

  • small dataset (upto X mb)
  • big dataset (upto Y gb)
  • enterprise class production BigData datasets (no limit)

Pricing of Software that can be used-

Ease of using Software

  • GUI vs Non GUI
  • Software that require not much extensive training
  • Software that require extensive training

Installation, Customization, Maintainability (or Support) for Software

  • Installation Dependencies- Size- Hardware (costs and  efficiencies)
  • Customization provided for specific use
  • Support Channels (including approximate Turn Around Time)

Software

  • Software I have used personally
  • SAS (Base, Stat,Enterprise,Connect,ETS) WPS KXEN SPSS (Base,Trends),Revolution R,R,Rapid Miner,Knime,JMP,SQL SERVER,Rattle, R Commander,Deducer
  • Software I know by reputation- SAS Enterprise Miner etc etc

Are there any other parameters for judging software?  let me know at http://twitter.com/decisionstats

Which software do we buy? -It depends

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Often I am asked by clients, friends and industry colleagues on the suitability or unsuitability of particular software for analytical needs.  My answer is mostly-

It depends on-

1) Cost of Type 1 error in purchase decision versus Type 2 error in Purchase Decision. (forgive me if I mix up Type 1 with Type 2 error- I do have some weird childhood learning disabilities which crop up now and then)

Here I define Type 1 error as paying more for a software when there were equivalent functionalities available at lower price, or buying components you do need , like SPSS Trends (when only SPSS Base is required) or SAS ETS, when only SAS/Stat would do.

The first kind is of course due to the presence of free tools with GUI like R, R Commander and Deducer (Rattle does have a 500$ commercial version).

The emergence of software vendors like WPS (for SAS language aficionados) which offer similar functionality as Base SAS, as well as the increasing convergence of business analytics (read predictive analytics), business intelligence (read reporting) has led to somewhat brand clutter in which all softwares promise to do everything at all different prices- though they all have specific strengths and weakness. To add to this, there are comparatively fewer business analytics independent analysts than say independent business intelligence analysts.

2) Type 2 Error- In this case the opportunity cost of delayed projects, business models , or lower accuracy – consequences of buying a lower priced software which had lesser functionality than you required.

To compound the magnitude of error 2, you are probably in some kind of vendor lock-in, your software budget is over because of buying too much or inappropriate software and hardware, and still you could do with some added help in business analytics. The fear of making a business critical error is a substantial reason why open source software have to work harder at proving them competent. This is because writing great software is not enough, we need great marketing to sell it, and great customer support to sustain it.

As Business Decisions are decisions made in the constraints of time, information and money- I will try to create a software purchase matrix based on my knowledge of known softwares (and unknown strengths and weakness), pricing (versus budgets), and ranges of data handling. I will add in basically an optimum approach based on known constraints, and add in flexibility for unknown operational constraints.

I will restrain this matrix to analytics software, though you could certainly extend it to other classes of enterprise software including big data databases, infrastructure and computing.

Noted Assumptions- 1) I am vendor neutral and do not suffer from subjective bias or affection for particular software (based on conferences, books, relationships,consulting etc)

2) All software have bugs so all need customer support.

3) All software have particular advantages , strengths and weakness in terms of functionality.

4) Cost includes total cost of ownership and opportunity cost of business analytics enabled decision.

5) All software marketing people will praise their own software- sometimes over-selling and mis-selling product bundles.

Software compared are SPSS, KXEN, R,SAS, WPS, Revolution R, SQL Server,  and various flavors and sub components within this. Optimized approach will include parallel programming, cloud computing, hardware costs, and dependent software costs.

To be continued-

 

 

 

 

Going Deap : Algols in Python

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Here is an important new step in Python- the established statistical programming language (used to be really pushed by SPSS in pre-IBM days and the rPy package integrates R and Python).

Well the news  ( http://www.kdnuggets.com/2010/10/eap-evolutionary-algorithms-in-python.html ) is the release of Distributed Evolutionary Algorithms in Python. If your understanding of modeling means running regression and iterating it- you may need to read some more.  If you have felt frustrated at lack of parallelization in statistical software as well as your own hardware constraints- well go DEAP (and for corporate types the licensing is

http://www.gnu.org/licenses/lgpl.html ).

http://code.google.com/p/deap/

DEAP

DEAP is intended to be an easy to use distributed evolutionary algorithm library in the Python language. Its two main components are modular and can be used separately. The first module is a Distributed Task Manager (DTM), which is intended to run on cluster of computers. The second part is the Evolutionary Algorithms in Python (EAP) framework.

DTM

DTM is a distributed task manager that is able to spread workload over a buch of computers using a TCP or a MPI connection.

DTM include the following features:

 

EAP

Features

EAP includes the following features:

  • Genetic algorithm using any imaginable representation
    • List, Array, Set, Dictionary, Tree, …
  • Genetic programing using prefix trees
    • Loosely typed, Strongly typed
    • Automatically defined functions (new v0.6)
  • Evolution strategies (including CMA-ES)
  • Multi-objective optimisation (NSGA-II, SPEA-II)
  • Parallelization of the evaluations (and maybe more) (requires python2.6 and preferably python2.7) (new v0.6)
  • Genealogy of an evolution (that is compatible with NetworkX) (new v0.6)
  • Hall of Fame of the best individuals that lived in the population (new v0.5)
  • Milestones that take snapshot of a system regularly (new v0.5)

 

Documentation

See the eap user’s guide for EAP 0.6 documentation.

Requirement

The most basic features of EAP requires Python2.5 (we simply do not offer support for 2.4). In order to use multiprocessing you will need Python2.6 and to be able to combine the toolbox and the multiprocessing module Python2.7 is needed for its support to pickle partial functions.

Projects using EAP

If you want your project listed here, simply send us a link and a brief description and we’ll be glad to add it.

and from the wordpress.com blog (funny how people like code.google.com but not blogger.google.com anymore) at http://deapdev.wordpress.com/

EAP is part of the DEAP project, that also includes some facilities for the automatic distribution and parallelization of tasks over a cluster of computers. The D part of DEAP, called DTM, is under intense development and currently available as an alpha version. DTM currently provides two and a half ways to distribute workload on a cluster or LAN of workstations, based on MPI and TCP communication managers.

This public release (version 0.6) is more complete and simpler than ever. It includes Genetic Algorithms using any imaginable representation, Genetic Programming with strongly and loosely typed trees in addition to automatically defined functions, Evolution Strategies (including Covariance Matrix Adaptation), multiobjective optimization techniques (NSGA-II and SPEA2), easy parallelization of algorithms and much more like milestones, genealogy, etc.

We are impatient to hear your feedback and comments on that system at .

Best,

François-Michel De Rainville
Félix-Antoine Fortin
Marc-André Gardner
Christian Gagné
Marc Parizeau

Laboratoire de vision et systèmes numériques
Département de génie électrique et génie informatique
Université Laval
Quebec City (Quebec), Canada

and if you are new to Python -sigh here are some statistical things (read ad-van-cED analytics using Python) by a slideshare from Visual numerics (pre Rogue Wave acquisition)

Also see,

http://code.google.com/p/deap/wiki/SimpleExample

 

 

 

Top ten RRReasons R is bad for you ?

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R stands for programming language based out of www.r-project.org

R is bad for you because –

1) It is slower with bigger datasets than SPSS language and SAS language .If you use bigger datasets, then you should either consider more hardware , or try and wait for some of the ODBC connect packages.

2) It needs more time to learn than SAS language .Much more time to learn how to do much more.

3) R programmers are lesser paid than SAS programmers.They prefer it that way.It equates the satisfaction of creating a package in development with a world wide community with the satisfaction of using a package and earning much more money per hour.

4) It forces you to learn the exact details of what you are doing due to its object oriented structure. Thus you either get no answer or get an exact answer. Your customer pays you by the hour not by the correct answers.

5) You can not push a couple of buttons or refer to a list of top ten most commonly used commands to finish the project.

6) It is free. And open for all. It is socialism expressed in code. Some of the packages are built by university professors. It is free.Free is bad. Who pays for the mortgage of the software programmers if all softwares were free ? Who pays for the Friday picnics. Who pays for the Good Night cruises?

7) It is free. Your organization will not commend you for saving them money- they will question why you did not recommend this before. And why did you approve all those packages that expire in 2011.R is fReeeeee. Customers feel good while spending money.The more software budgets you approve the more your salary is. R thReatens all that.

8) It is impossible to install a package you do not need or want. There is no one calling you on the phone to consider one more package or solution. R can make you lonely.

9) R uses mostly Command line. Command line is from the Seventies. Or the Eighties. The GUI’s RCmdr and Rattle are there but still…..

10) R forces you to learn new stuff by the month. You prefer to only earn by the month. Till the day your job got offshored…

Written by a R user in English language

( which fortunately was not copyrighted otherwise we would be paying Britain for each word)

Ajay- The above post was reprinted by personal request. It was written on Jan 2009- and may not be truly valid now. It is meant to be taken in good humor-not so seriously.

Top R Interviews

 

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Here is a list of the Top R Related Interviews I have done (in random order)-

1) John Fox , Creator of R Commander

https://decisionstats.com/2009/09/14/interview-professor-john-fox-creator-r-commander/

2) Dr Graham Williams, Creator of Rattle

https://decisionstats.com/2009/01/13/interview-dr-graham-williams/

3) David Smith, back when he was community Director of then Revolution Computing.

https://decisionstats.com/2009/05/29/interview-david-smith-revolution-computing/

and his second interview

https://decisionstats.com/2010/08/03/q-a-with-david-smith-revolution-analytics/

4) Robert Schultz, the first CEO of Revolution Computing (now Analytics)

https://decisionstats.com/2009/01/31/interviewrichard-schultz-ceo-revolution-computing/

5) Bob  Muenchen, author of R for SAS and SPSS users AND R for Stata users

https://decisionstats.com/2010/06/29/interview-r-for-stata-users/

https://decisionstats.com/2008/10/16/r-for-sas-and-spss-users/

6) Karim Chine, creator Biocep, Cloud Computing for R

https://decisionstats.com/2009/06/21/interview-karim-chine-biocep-cloud-computing-with-r/

7) Paul van Eikeran, Inference for R,the first enterprise package to use R from within MS Office.

https://decisionstats.com/2009/06/04/inference-for-r/

8) Hadley Wickham, creator GGPlot and R Author

https://decisionstats.com/2010/01/12/interview-hadley-wickham-r-project-data-visualization-guru/

Thats a lot of R interviews- I need to balance them out a bit I guess.

IBM Business Analytics Forum

IBM Cognos is about to be launced next month, and Cognos Forum and SPSS Directions have merged to form Business Analytics Forum.

Cognos and SPSS bundled together is a formidable software package for business analysts.

See http://www-01.ibm.com/software/data/2010-conference/business-analytics/