Tag: data

Interview- Top Data Mining Blogger on Earth , Sandro Saitta

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If you do a Google search for Data Mining Blog- for the past several years one Blog will come on top. data mining blog – Google Search http://bit.ly/kEdPlE

To honor 5 years of Sandro Saitta’s blog (yes thats 5 years!) , we cover an exclusive interview with him where he reveals his unique sauce for cool techie blogging.

Ajay- Describe your journey as a scientist and data miner, from early experiences, to schooling to your work/research/blogging.

Sandro- My first experience with data mining was my master project. I used decision tree to predict pollen concentration for the following week using input data such as wind, temperature and rain. The fact that an algorithm can make a computer learn from experience was really amazing to me. I found it so interesting that I started a PhD in data mining. This time, the field of application was civil engineering. Civil engineers put a lot of sensors on their structure in order to understand how they behave. With all these sensors they generate a lot of data. To interpret these data, I used data mining techniques such as feature selection and clustering. I started my blog, Data Mining Research, during my PhD, to share with other researchers.

I then started applying data mining in the stock market as my first job in industry. I realized the difference between image recognition, where 99% correct classification rate is state of the art, and stock market, where you’re happy with 55%. However, the company ambiance was not as good as I thought, so I moved to consulting. There, I applied data mining in behavioral targeting to increase click-through rates. When you compare the number of customers who click with the ones who don’t, then you really understand what class imbalance mean. A few months ago, I accepted a very good opportunity at SICPA. I’m looking forward to resolving new challenges there.

Ajay- Your blog is the top ranked blog for “data mining blog”. Could you share some tips on better blogging for analytics and technical people

Sandro- It’s always difficult to start a blog, since at the beginning you have no reader. Writing for nobody may seem stupid, but it is not. By writing my first posts during my PhD I was reorganizing my ideas. I was expressing concepts which were not always clear to me. I thus learned a lot and also improved my English level. Of course, it’s still not perfect, but I hope most people can understand me.

Next come the readers. A few dozen each week first. To increase this number, I then started to learn SEO (Search Engine Optimization) by reading books and blogs. I tested many techniques that increased Data Mining Research visibility in the blogosphere. I think SEO is interesting when you already have some content published (which means not at the very beginning of your blog). After a while, once your blog is nicely ranked, the main task is to work on the content of the blog. To be of interest, your content must be particular: original, informative or provocative for example. I also had the chance to have a good visibility thanks to well-known people in the field like Kevin Hillstrom, Gregory Piatetsky-Shapiro, Will Dwinnell / Dean Abbott, Vincent Granville, Matthew Hurst and many others.

Ajay- Whats your favorite statistical software and what are the various softwares that you have worked with.
Could you compare and contrast these software as well.

Sandro- My favorite software at this point is SAS. I worked with it for two years. Once you know the language, you can perform ETL and data mining so easily. It’s also very fast compared to others. There are a lot of tools for data mining, but I cannot think of a tool that is as powerful as SAS and, in the same time, has a high-level programming language behind it.

I also worked with R and Matlab. R is very nice since you have all the up-to-date data mining algorithms implemented. However, working in the memory is not always a good choice, especially for ETL. Matlab is an excellent tool for prototyping. It’s not so fast and certainly not done for ETL, but the price is low regarding all the possibilities for data mining. According to me, SAS is the best choice for ETL and a good choice for data mining. Of course, there is the price.

Ajay- What are your favorite techniques and training resources for learning basics of data mining to say statisticians or business management graduates.

Sandro- I’m the kind of guy who likes to read books. I read data mining books one after the other. The fact that the same concepts are explained differently (and by different people) helps a lot in learning a topic like data mining. Of course, nothing replaces experience in the field. You can read hundreds of books, you will still not be a good practitioner until you really apply data mining in specific fields. My second choice after books is blogs. By reading data mining blogs, you will really see the issues and challenges in the field. It’s still not experience, but we are closer. Finally, web resources and networks such as KDnuggets of course, but also AnalyticBridge and LinkedIn.

Ajay- Describe your hobbies and how they help you ,if at all in your professional life.

Sandro- One of my hobbies is reading. I read a lot of books about data mining, SEO, Google as well as Sci-Fi and Fantasy. I’m a big fan of Asimov by the way. My other hobby is playing tennis. I think I simply use my hobbies as a way to find equilibrium in my life. I always try to find the best balance between work, family, friends and sport.

Ajay- What are your plans for your website for 2011-2012.

Sandro- I will continue to publish guest posts and interviews. I think it is important to let other people express themselves about data mining topics. I will not write about my current applications due to the policies of my current employer. But don’t worry, I still have a lot to write, whether it is technical or not. I will also emphasis more on my experience with data mining, advices for data miners, tips and tricks, and of course book reviews!

Standard Disclosure of Blogging- Sandro awarded me the Peoples Choice award for his blog for 2010 and carried out my interview. There is a lot of love between our respective wordpress blogs, but to reassure our puritan American readers- it is platonic and intellectual.

About Sandro S-



Sandro Saitta is a Data Mining Research Engineer at SICPA Security Solutions. He is also a blogger at Data Mining Research (www.dataminingblog.com). His interests include data mining, machine learning, search engine optimization and website marketing.

You can contact Mr Saitta at his Twitter address- 

https://twitter.com/#!/dataminingblog

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Who writes white papers?

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There are four main types of commercial white papers:

  • Business benefits: Makes a business case for a certain technology or methodology.
  • Technical: Describes how a certain technology works.
  • Hybrid: Combines business benefits with technical details in a single document.
  • Policy: Makes a case for a certain political solution to a societal or economic challenge.
Name the best white paper you ever read? (comment that in the field)..
What categoy of white papers is the best?
Do you think white papers are too expensive or they give adequate ROI?
To be continued- including

  1. demographic and social network analysis of analysts and white paper sponsors to measure interaction effects.
  2. white papers segmented by type of software company
  3. proc freq analysis of the words frequency data viz in white papers written by same analysts for different companies on same topics.
  4. Race and ethnic analysis of influencers and analysts in Business Analysts and Business Intelligence. – Null hypothesis – it is not a white mans world, women, Hispanics and other minorities are adequately represented.
Why I am doing this?
I am writing a white paper on WHO writes a white paper? 
Sponsorships are invited- but academics and startups in analytics may be preferred.
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#Rstats gets into Enterprise Cloud Software

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Here is an excellent example of how websites should help rather than hinder new customers take a demo of the software without being overwhelmed by sweet talking marketing guys who dont know the difference between heteroskedasticity, probability, odds and likelihood.

It is made by Zementis (Dr Michael Zeller has been a frequent guest here) and Revolution Analytics is still the best shot in Enterprise software for #Rstats

Now if only Revo could get into the lucrative Department of Energy or Department of Defense business- they could change the world AND earn some more revenue than they have been doing. But seriously.

Check out http://deployr.revolutionanalytics.com/zementis/ and play with it. or better still mash it with some data viz and ROC curves.- or extend it with some APIS 😉

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Analyzing Judas of Lady Gaga

Youtube, the big tube of the fat pipes of the internet’s shallow side (we shall discuss the deep Dark Net later)-

well Youtube enhanced video analytics greatly.

Have a look at Lady Gaga Judas video analytics data viz- do you think you can pack more or better data viz here.

Analytics is great- but Youtube please be a dear and hire some graphics designers once in a while. Nopes- not the ones your engineers are dating, but real graphics designers.

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Tom Davenport to Keynote at PAW New York

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message from Predictive Analytics World. If you are NY based you may want to drop in and listen.———————————————————————————-Tom Davenport to Keynote at
Predictive Analytics World New York
Take advantage of Super Early Bird Pricing by May 20th and recognize savings of $400. Additional savings when you bring the team*

Announcing Tom Davenport Keynote:
Thomas Davenport Every Day Analytics:
Making Leading Edge CommonplaceThomas Davenport
President’s Distinguished Prof, Babson College
Author, Competing on Analytics & Analytics at Work

Join your peers October 17-21, 2011 at the Hilton New York for Predictive Analytics World, the business event for predictive analytics professionals, managers and commercial practitioners, covering today’s commercial deployment of predictive analytics, across industries and across software vendors.

PAW NYC promises to once again break records as the biggest cross-vendor predictive analytics event ever. The conference program is packed with the top predictive analytics experts, practitioners, authors and business thought leaders, including keynote addresses from Thomas Davenport, author of Competing on Analytics: The New Science of Winning, and PAW Program Chair Eric Siegel, plus special sessions from industry heavy-weights Usama Fayyad and John Elder.
RAVE REVIEWS:“I came to PAW because it provides case studies relevant to my industry. It has lived up to the expectation and I think it’s the best analytics conference I’ve ever attended!“

Shaohua Zhang, Senior Data Mining Analyst
Rogers Telecommunications

“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

PAW NYC’s agenda covers black box trading, churn modeling, crowdsourcing, demand forecasting, ensemble models, fraud detection, healthcare, insurance applications, law enforcement, litigation, market mix modeling, mobile analytics, online marketing, risk management, social data, supply chain management, targeting direct marketing, uplift modeling (net lift), and other innovative applications that benefit organizations in new and creative ways.

Take advantage of Super Early Bird Pricing and realize
$400 in savings before May 20, 2011.

Note:  Each additional attendee from the same company registered at the same time receives an extra $200 off the Conference Pass.

Register Now!

eMetrics New York
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Heritage offers 3 million chump change for Monkeys

My perspective is life is not fair, and if someone offers me 1 mill a year so they make 1 bill a year, I would still take it, especially if it leads to better human beings and better humanity on this planet. Health care isnt toothpaste.

Unless there are even more fine print changes involved- there exist several players in the pharma sector who do build and deploy models internally for denying claims or prospecting medical doctors with freebies, but they might just get caught with the new open data movement

————————————————————————————————–

A note from KDNuggets-

Heritage Health Prizereleased a second set of data on May 4. They also recently modified their ruleswhich now demand complete exclusivity and seem to disallow use of other tools (emphasis mine – Gregory PS)

21. LICENSE
By registering for the Competition, each Entrant (a) grants to Sponsor and its designees a worldwide, exclusive (except with respect to Entrant) , sub-licensable (through multiple tiers), transferable, fully paid-up, royalty-free, perpetual, irrevocable right to use, not use, reproduce, distribute (through multiple tiers), create derivative works of, publicly perform, publicly display, digitally perform, make, have made, sell, offer for sale and import the entry and the algorithm used to produce the entry, as well as any other algorithm, data or other information whatsoever developed or produced at any time using the data provided to Entrant in this Competition (collectively, the “Licensed Materials”), in any media now known or hereafter developed, for any purpose whatsoever, commercial or otherwise, without further approval by or payment to Entrant (the “License”) and
(b) represents that he/she/it has the unrestricted right to grant the License. 
Entrant understands and agrees that the License is exclusive except with respect to Entrant: Entrant may use the Licensed Materials solely for his/her/its own patient management and other internal business purposes but may not grant or otherwise transfer to any third party any rights to or interests in the Licensed Materials whatsoever.

This has lead to a call to boycott the competition by Tristan, who also notes that academics cannot publish their results without prior written approval of the Sponsor.

Anthony Goldbloom, CEO of Kaggle, emailed the HHP participants on May 4

HPN have asked me to pass on the following message: “The Heritage Provider Network is sponsoring the Heritage Health Prize to spur innovation and creative thinking in healthcare. HPN, however, is a medical group and must retain an exclusive license to the algorithms created using its data so as to ensure that the algorithms are used responsibly, and are only used to provide better health care to patients and not for improper purposes.
Put simply, while the competition hopes to spur innovation, this is not a competition regarding movie ratings or chess results. We hope that the clarifications we have made to the Rules and the FAQ adequately address your concerns and look forward to your participation in the competition.”

What do you think? Will the exclusive license prevent you from participating?

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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 Journal, The Economist, Slate 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.

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