Heritage prize= 3mill now open

I am still angry with THE netflix for 1 mill I lost out. No sweat! this time the money is 3 times as much, it is legit, and yes baby you can change the world, make it a better place and get rich.! see details below-http://www.heritagehealthprize.com/c/hhp/Data

HERITAGE HEALTH PRIZE DATA FILES

You must accept this competition’s rules before you’ll be able to download data files.

IMPORTANT NOTE: The information provided below is intended only to provide general guidance to participants in the Heritage Health Prize Competition and is subject to the Competition Official Rules. Any capitalized term not defined below is defined in the Competition Official Rules. Please consult the Competition Official Rules for complete details.

Heritage Provider Network is providing Competition Entrants with deidentified member data collected during a forty-eight month period that is allocated among three data sets (the “Data Sets”). Competition Entrants will use the Data Sets to develop and test their algorithms for accurately predicting the number of days that the members will spend in a hospital (inpatient or emergency room visit) during the 12-month period following the Data Set cut-off date.

HHP_release2.zip contains the latest files, so you can ignore HHP_release1.zip. SampleEntry.CSV shows you how an entry should look.

Data Sets will be released to Entrants after registration on the Website according to the following schedule:

April 4, 2011 Claims Table – Y1 and DaysInHospital Table – Y2

May 4, 2011

All other Data Sets except Labs Table and Rx Table

From https://www.kaggle.com/

The $3 million Heritage Health Prize opens to entries

It’s been one month since the launch of the Heritage Health Prize. The prize has attracted some great publicity, receiving coverage from the Wall Street JournalThe EconomistSlate andForbes.

By now, people have had a good chance to poke around the first portion of the data. Now the fun starts! HPN have released two more years’-worth of data, set the accuracy threshold and are opening up the competition to entries. The data are available from the Heritage Health Prize page. Good luck to all participants!

The Deloitte/FIDE Chess Ratings Competition results

The Deloitte/FIDE Chess Ratings Competition attracted one of the strongest fields ever seen in a Kaggle Competition. The competition attracted 189 teams, ranging from chess ratings  experts to Netflix Prize winners. As Jeff Sonas wrote on the Kaggle blog last week, the  competition has far exceeded his expectations. A big congratulations the provisional winner, Tim Salimans, an econometrician at Erasmus University in Rotterdam. We look forward to reading about the approaches used by top performers on the Kaggle blog. We also look forward to the results of the FIDE prize, which could see the introduction of a new chess ratings system.

ICDAR 2011 Competition Results

The ICDAR 2011 competition also finished recently. The competiiton required participants to develop an algorithm that correctly matched handwriting samples. The winners were Lewis Griffin and Andrew Newell from the University College London who achieved Kaggle’s first ever perfect score by managing to match every sample correctly! Andrew and Lewis have posted a description of their winning method on the Kaggle blog.

Revolution R Enterprise

Since R is the most popular language used by Kaggle members, the Revolution Analytics team is making Revolution R Enterprise (the pre-eminent commercial version of R) available free of charge to Kaggle members. Revolution R Enterprise has several advantages over standard R, including the ability to seemlessly handle larger datasets. To get your free copy, visit http://info.revolutionanalytics.com/Kaggle.html.
Kaggle-in-Class

As many of you know, Kaggle offers a free platform, Kaggle-in-Class, for instructors who want to host competitions for their students. For those interested in hearing more about the use of Kaggle-in-Class as a teaching tool, Susan Holmes and Nelson Ray from Stanford University share their experience in a webinar organized by the Consortium for the Advancement of Undergraduate Statistics Education.

Google Storage for Developers goes into Enterprise Mode

Schematic representation of the SSL handshake ...
Image via Wikipedia

To help unify and uniform, collobrative work and data management and business models across the enterprise in secure SSL cloud environments- Google Storage has been rolling out some changes (read below)-this also gives you more options on the day Amazon goes ahem down (cough cough) because they didn’t think someone in their data environment could be sympathetic to free data.

——————————————————————————————————————————————————————–

https://groups.google.com/group/gs-announce

And now to the actual update.

We’re making some changes to Google Storage for Developers to make team-based development easier. As part of this work, we are introducing the concept of a project. In preparation for this feature, we will be creating projects for every user and migrating their buckets to it.

What does this mean for you?

Everything will continue to work as it always has. However, you will notice that if you perform a get-acl operation on any of your buckets, you will see extra ACL entries. These entries correspond to project groups. Each group has only one member – the person who owned the buckets before the bucket migration;  no additional rights have been granted to any of your buckets or objects. You should preserve these new ACL grants if you modify bucket ACLs.

An example entry for a modified ACL would look like this:

We’ll be rolling out these changes over the next few days,

http://blog.cloudberrylab.com/2011/04/cloudberry-explorer-for-google-storage.html

Detailed Note on GS-

https://code.google.com/apis/storage/

Google Storage for Developers is a RESTful service for storing and accessing your data on Google’s infrastructure. The service combines the performance and scalability of Google’s cloud with advanced security and sharing capabilities. Highlights include:

Fast, scalable, highly available object store

  • All data replicated to multiple U.S. data centers
  • Read-your-writes data consistency
  • Objects of hundreds of gigabytes in size per request with range-get support
  • Domain-scoped bucket namespace

Easy, flexible authentication and sharing

  • Key-based authentication
  • Authenticated downloads from a web browser
  • Individual- and group-level access controls

In addition, Google Storage for Developers offers a web-based interface for managing your storage and GSUtil, an open source command line tool and library. The service is also compatible with many existing cloud storage tools and libraries. With pay-as-you-go pricing, it’s easy to get started and scale as your needs grow.

Google Storage for Developers is currently only available to a limited number of developers. Please sign up to join the waiting list.

Revolution releases R Windows for Academics for free

Logo for R
Image via Wikipedia

Based on the official email from them, God bless the merry coders at Revo-

Revolution Analytics has just released Revolution R Enterprise 4.3 for 32-bit and 64-bit Windows, a significant step forward in enterprise data analytics.  It features an updated RevoScaleR package for scalable, fast (multicore), and extensible data analysis with R. Revolution R Enterprise 4.3 for Windows also provides R 2.12.2, and includes an enhanced R Productivity Environment (RPE), a full-featured integrated development environment with visual debugging capabilities. Also available is an updated Windows release of our deployment server solution, RevoDeployR 1.2, designed to help you deliver R analytics via the Web.

As a registered user of the Academic version of Revolution R Enterprise for Windows, you can take advantage of these improvements by downloading and installing Revolution R Enterprise 4.3 today. You can install Revolution R Enterprise 4.3 side-by-side with your existing Revolution R Enterprise installations; there is no need to uninstall previous versions.

 

Free and Open Source cannot get basic economics correct

Nutch robots
Image via Wikipedia

Before you rev up those keyboards, and shoot off a snarky comment- consider this statement- there are many ways to run (and ruin economies). But they still have not found a replacement for money. Yes Happiness is important. Search Engine is good.

So unless they start a new branch of economics with lots more motivational theory and psychology and lot less quant especially for open source projects, money ,revenue, sales is the only true measure of success in enterprise software. Particularly if you have competitors who are making more money selling the same class of software.

Popularity contests are for high school quarterbacks —so even if your open source software is popular in downloads, email discussions, stack overflow or Continue reading “Free and Open Source cannot get basic economics correct”

High Performance Analytics

Marry Big Data Analytics to High Performance Computing, and you get the buzzword of this season- High Performance Analytics.

It basically consists of Parallelized code to run in parallel on custom hardware, in -database analytics for speed, and cloud computing /high performance computing environments. On an operational level, it consists of software (as in analytics) partnering with software (as in databases, Map reduce, Hadoop) plus some hardware (HP or IBM mostly). It is considered a high margin , highly profitable, business with small number of deals compared to say desktop licenses.

As per HPC Wire- which is a great tool/newsletter to keep updated on HPC , SAS Institute has been busy on this front partnering with EMC Greenplum and TeraData (who also acquired  SAS Partner AsterData to gain a much needed foot in the MR/SQL space) Continue reading “High Performance Analytics”

Predictive Analytics World Conference –New York City and London, UK

Please use the following code  to get a 15% discount on the 2 Day Conference Pass:  AJAYNY11.

Predictive Analytics World Conference –New York City and London, UK

October 17-21, 2011 – New York City, NY (pawcon.com/nyc)
Nov 30 – Dec 1, 2011 – London, UK (pawcon.com/london)

Predictive Analytics World (pawcon.com) is the business-focused event for predictive analytics
professionals, managers and commercial practitioners, covering today’s commercial deployment of
predictive analytics, across industries and across software vendors. The conference delivers case
studies, expertise, and resources to achieve two objectives:

1) Bigger wins: Strengthen the business impact delivered by predictive analytics

2) Broader capabilities: Establish new opportunities with predictive analytics

Case Studies: How the Leading Enterprises Do It

Predictive Analytics World focuses on concrete examples of deployed predictive analytics. The leading
enterprises have signed up to tell their stories, so you can hear from the horse’s mouth precisely how
Fortune 500 analytics competitors and other top practitioners deploy predictive modeling, and what
kind of business impact it delivers.

PAW NEW YORK CITY 2011

PAW’s NYC program is the richest and most diverse yet, featuring over 40 sessions across three tracks
– including both X and Y tracks, and an “Expert/Practitioner” track — so you can witness how predictive
analytics is applied at major companies.

PAW NYC’s agenda covers hot topics and advanced methods such as ensemble models, social data,
search marketing, crowdsourcing, blackbox trading, fraud detection, risk management, survey analysis,
and other innovative applications that benefit organizations in new and creative ways.

WORKSHOPS: PAW NYC also features five full-day pre- and post-conference workshops that
complement the core conference program. Workshop agendas include advanced predictive modeling
methods, hands-on training, an intro to R (the open source analytics system), and enterprise decision
management.

For more see http://www.predictiveanalyticsworld.com/newyork/2011/

PAW LONDON 2011

PAW London’s agenda covers hot topics and advanced methods such as risk management, uplift
(incremental lift) modeling, open source analytics, and crowdsourcing data mining. Case study
presentations cover campaign targeting, churn modeling, next-best-offer, selecting marketing channels,
global analytics deployment, email marketing, HR candidate search, and other innovative applications
that benefit organizations in new and creative ways.

Join PAW and access the best keynotes, sessions, workshops, exposition, expert panel, live demos,
networking coffee breaks, reception, birds-of-a-feather lunches, brand-name enterprise leaders, and

industry heavyweights in the business.

For more see http://www.predictiveanalyticsworld.com/london

CROSS-INDUSTRY APPLICATIONS

Predictive Analytics World is the only conference of its kind, delivering vendor-neutral sessions across
verticals such as banking, financial services, e-commerce, education, government, healthcare, high
technology, insurance, non-profits, publishing, social gaming, retail and telecommunications

And PAW covers the gamut of commercial applications of predictive analytics, including response
modeling, customer retention with churn modeling, product recommendations, fraud detection, online
marketing optimization, human resource decision-making, law enforcement, sales forecasting, and
credit scoring.

Why bring together such a wide range of endeavors? No matter how you use predictive analytics, the
story is the same: Predicatively scoring customers optimizes business performance. Predictive analytics
initiatives across industries leverage the same core predictive modeling technology, share similar project
overhead and data requirements, and face common process challenges and analytical hurdles.

RAVE REVIEWS:

“Hands down, best applied, analytics conference I have ever attended. Great exposure to cutting-edge
predictive techniques and I was able to turn around and apply some of those learnings to my work
immediately. I’ve never been able to say that after any conference I’ve attended before!”

Jon Francis
Senior Statistician
T-Mobile

Read more: Articles and blog entries about PAW can be found at http://www.predictiveanalyticsworld.com/
pressroom.php

VENDORS. Meet the vendors and learn about their solutions, software and service. Discover the best
predictive analytics vendors available to serve your needs – learn what they do and see how they
compare

COLLEAGUES. Mingle, network and hang out with your best and brightest colleagues. Exchange
experiences over lunch, coffee breaks and the conference reception connecting with those professionals
who face the same challenges as you.

GET STARTED. If you’re new to predictive analytics, kicking off a new initiative, or exploring new ways
to position it at your organization, there’s no better place to get your bearings than Predictive Analytics
World. See what other companies are doing, witness vendor demos, participate in discussions with the
experts, network with your colleagues and weigh your options!

For more information:
http://www.predictiveanalyticsworld.com

View videos of PAW Washington DC, Oct 2010 — now available on-demand:
http://www.predictiveanalyticsworld.com/online-video.php

What is predictive analytics? See the Predictive Analytics Guide:
http://www.predictiveanalyticsworld.com/predictive_analytics.php

If you’d like our informative event updates, sign up at:
http://www.predictiveanalyticsworld.com/signup-us.php

To sign up for the PAW group on LinkedIn, see:
http://www.linkedin.com/e/gis/1005097

For inquiries e-mail regsupport@risingmedia.com or call (717) 798-3495.

Augustus- a PMML model producer and consumer. Scoring engine.

A Bold GNU Head
Image via Wikipedia

I just checked out this new software for making PMML models. It is called Augustus and is created by the Open Data Group (http://opendatagroup.com/) , which is headed by Robert Grossman, who was the first proponent of using R on Amazon Ec2.

Probably someone like Zementis ( http://adapasupport.zementis.com/ ) can use this to further test , enhance or benchmark on the Ec2. They did have a joint webinar with Revolution Analytics recently.

https://code.google.com/p/augustus/

Recent News

  • Augustus v 0.4.3.1 has been released
  • Added a guide (pdf) for including Augustus in the Windows System Properties.
  • Updated the install documentation.
  • Augustus 2010.II (Summer) release is available. This is v 0.4.2.0. More information is here.
  • Added performance discussion concerning the optional cyclic garbage collection.

See Recent News for more details and all recent news.

Augustus

Augustus is a PMML 4-compliant scoring engine that works with segmented models. Augustus is designed for use with statistical and data mining models. The new release provides Baseline, Tree and Naive-Bayes producers and consumers.

There is also a version for use with PMML 3 models. It is able to produce and consume models with 10,000s of segments and conforms to a PMML draft RFC for segmented models and ensembles of models. It supports Baseline, Regression, Tree and Naive-Bayes.

Augustus is written in Python and is freely available under the GNU General Public License, version 2.

See the page Which version is right for me for more details regarding the different versions.

PMML

Predictive Model Markup Language (PMML) is an XML mark up language to describe statistical and data mining models. PMML describes the inputs to data mining models, the transformations used to prepare data for data mining, and the parameters which define the models themselves. It is used for a wide variety of applications, including applications in finance, e-business, direct marketing, manufacturing, and defense. PMML is often used so that systems which create statistical and data mining models (“PMML Producers”) can easily inter-operate with systems which deploy PMML models for scoring or other operational purposes (“PMML Consumers”).

Change Detection using Augustus

For information regarding using Augustus with Change Detection and Health and Status Monitoring, please see change-detection.

Open Data

Open Data Group provides management consulting services, outsourced analytical services, analytic staffing, and expert witnesses broadly related to data and analytics. It has experience with customer data, supplier data, financial and trading data, and data from internal business processes.

It has staff in Chicago and San Francisco and clients throughout the U.S. Open Data Group began operations in 2002.


Overview

The above example contains plots generated in R of scoring results from Augustus. Each point on the graph represents a use of the scoring engine and a chart is an aggregation of multiple Augustus runs. A Baseline (Change Detection) model was used to score data with multiple segments.

Typical Use

Augustus is typically used to construct models and score data with models. Augustus includes a dedicated application for creating, or producing, predictive models rendered as PMML-compliant files. Scoring is accomplished by consuming PMML-compliant files describing an appropriate model. Augustus provides a dedicated application for scoring data with four classes of models, Baseline (Change Detection) ModelsTree ModelsRegression Models and Naive Bayes Models. The typical model development and use cycle with Augustus is as follows:

  1. Identify suitable data with which to construct a new model.
  2. Provide a model schema which proscribes the requirements for the model.
  3. Run the Augustus producer to obtain a new model.
  4. Run the Augustus consumer on new data to effect scoring.

Separate consumer and producer applications are supplied for Baseline (Change Detection) models, Tree models, Regression models and for Naive Bayes models. The producer and consumer applications require configuration with XML-formatted files. The specification of the configuration files and model schema are detailed below. The consumers provide for some configurability of the output but users will often provide additional post-processing to render the output according to their needs. A variety of mechanisms exist for transmitting data but user’s may need to provide their own preprocessing to accommodate their particular data source.

In addition to the producer and consumer applications, Augustus is conceptually structured and provided with libraries which are relevant to the development and use of Predictive Models. Broadly speaking, these consist of components that address the use of PMML and components that are specific to Augustus.

Post Processing

Augustus can accommodate a post-processing step. While not necessary, it is often useful to

  • Re-normalize the scoring results or performing an additional transformation.
  • Supplements the results with global meta-data such as timestamps.
  • Formatting of the results.
  • Select certain interesting values from the results.
  • Restructure the data for use with other applications.