Using Rapid Miner and R for Sports Analytics #rstats

Rapid Miner has been one of the oldest open source analytics software, long long before open source or even analytics was considered a fashion buzzword. The Rapid Miner software has been a pioneer in many areas (like establishing a marketplace for Rapid Miner Extensions) and the Rapid Miner -R extension was one of the most promising enablers of using R in an enterprise setting.
The following interview was taken with a manager of analytics for a sports organization. The sports organization considers analytics as a strategic differentiator , hence the name is confidential. No part of the interview has been edited or manipulated.

Ajay- Why did you choose Rapid Miner and R? What were the other software alternatives you considered and discarded?

Analyst- We considered most of the other major players in statistics/data mining or enterprise BI.  However, we found that the value proposition for an open source solution was too compelling to justify the premium pricing that the commercial solutions would have required.  The widespread adoption of R and the variety of packages and algorithms available for it, made it an easy choice.  We liked RapidMiner as a way to design structured, repeatable processes, and the ability to optimize learner parameters in a systematic way.  It also handled large data sets better than R on 32-bit Windows did.  The GUI, particularly when 5.0 was released, made it more usable than R for analysts who weren’t experienced programmers.

Ajay- What analytics do you do think Rapid Miner and R are best suited for?

 Analyst- We use RM+R mainly for sports analysis so far, rather than for more traditional business applications.  It has been quite suitable for that, and I can easily see how it would be used for other types of applications.

 Ajay- Any experiences as an enterprise customer? How was the installation process? How good is the enterprise level support?

Analyst- Rapid-I has been one of the most responsive tech companies I’ve dealt with, either in my current role or with previous employers.  They are small enough to be able to respond quickly to requests, and in more than one case, have fixed a problem, or added a small feature we needed within a matter of days.  In other cases, we have contracted with them to add larger pieces of specific functionality we needed at reasonable consulting rates.  Those features are added to the mainline product, and become fully supported through regular channels.  The longer consulting projects have typically had a turnaround of just a few weeks.

 Ajay- What challenges if any did you face in executing a pure open source analytics bundle ?

Analyst- As Rapid-I is a smaller company based in Europe, the availability of training and consulting in the USA isn’t as extensive as for the major enterprise software players, and the time zone differences sometimes slow down the communications cycle.  There were times where we were the first customer to attempt a specific integration point in our technical environment, and with no prior experiences to fall back on, we had to work with Rapid-I to figure out how to do it.  Compared to the what traditional software vendors provide, both R and RM tend to have sparse, terse, occasionally incomplete documentation.  The situation is getting better, but still lags behind what the traditional enterprise software vendors provide.

 Ajay- What are the things you can do in R ,and what are the things you prefer to do in Rapid Miner (comparison for technical synergies)

Analyst- Our experience has been that RM is superior to R at writing and maintaining structured processes, better at handling larger amounts of data, and more flexible at fine-tuning model parameters automatically.  The biggest limitation we’ve had with RM compared to R is that R has a larger library of user-contributed packages for additional data mining algorithms.  Sometimes we opted to use R because RM hadn’t yet implemented a specific algorithm.  The introduction the R extension has allowed us to combine the strengths of both tools in a very logical and productive way.

In particular, extending RapidMiner with R helped address RM’s weakness in the breadth of algorithms, because it brings the entire R ecosystem into RM (similar to how Rapid-I implemented much of the Weka library early on in RM’s development).  Further, because the R user community releases packages that implement new techniques faster than the enterprise vendors can, this helps turn a potential weakness into a potential strength.  However, R packages tend to be of varying quality, and are more prone to go stale due to lack of support/bug fixes.  This depends heavily on the package’s maintainer and its prevalence of use in the R community.  So when RapidMiner has a learner with a native implementation, it’s usually better to use it than the R equivalent.

RCOMM 2012 goes live in August

An awesome conference by an awesome software Rapid Miner remains one of the leading enterprise grade open source software , that can help you do a lot of things including flow driven data modeling ,web mining ,web crawling etc which even other software cant.

Presentations include:

  • Mining Machine 2 Machine Data (Katharina Morik, TU Dortmund University)
  • Handling Big Data (Andras Benczur, MTA SZTAKI)
  • Introduction of RapidAnalytics at Telenor (Telenor and United Consult)
  • and more

Here is a list of complete program

 

Program

 

Time
Slot
Tuesday
Training / Workshop 1
Wednesday
Conference 1
Thursday
Conference 2
Friday
Training / Workshop 2
09:00 – 10:30
Introductory Speech
Ingo Mierswa (Rapid-I)Resource-aware Data Mining or M2M Mining (Invited Talk)

Katharina Morik (TU Dortmund University)

More information

 

Data Analysis

 

NeurophRM: Integration of the Neuroph framework into RapidMiner
Miloš Jovanović, Jelena Stojanović, Milan Vukićević, Vera Stojanović, Boris Delibašić (University of Belgrade)

To be announced (Invited Talk)
Andras Benczur 

Recommender Systems

 

Extending RapidMiner with Recommender Systems Algorithms
Matej Mihelčić, Nino Antulov-Fantulin, Matko Bošnjak, Tomislav Šmuc (Ruđer Bošković Institute)

Implementation of User Based Collaborative Filtering in RapidMiner
Sérgio Morais, Carlos Soares (Universidade do Porto)

Parallel Training / Workshop Session

Advanced Data Mining and Data Transformations

or

Development Workshop Part 2

10:30 – 11:00
Coffee Break
Coffee Break
Coffee Break
11:00 – 12:30
Data Analysis

Nearest-Neighbor and Clustering based Anomaly Detection Algorithms for RapidMiner
Mennatallah Amer, Markus Goldstein (DFKI)

Customers’ LifeStyle Targeting on Big Data using Rapid Miner
Maksim Drobyshev (LifeStyle Marketing Ltd)

Robust GPGPU Plugin Development for RapidMiner
Andor Kovács, Zoltán Prekopcsák (Budapest University of Technology and Economics)

Extensions

 

Optimization Plugin For RapidMiner
Venkatesh Umaashankar, Sangkyun Lee (TU Dortmund University; presented by Hendrik Blom)

 

Image Mining Extension – Year After
Radim Burget, Václav Uher, Jan Mašek (Brno University of Technology)

Incorporating R Plots into RapidMiner Reports
Peter Jeszenszky (University of Debrecen)

12:30 – 13:30
Lunch
Lunch
Lunch
13:30 – 15:30
Parallel Training / Workshop Session

Basic Data Mining and Data Transformations

or

Development Workshop Part 1

Applications

 

Introduction of RapidAnalyticy Enterprise Edition at Telenor Hungary
t.b.a. (Telenor Hungary and United Consult)

 

Application of RapidMiner in Steel Industry Research and Development
Bengt-Henning Maas, Hakan Koc, Martin Bretschneider (Salzgitter Mannesmann Forschung)

A Comparison of Data-driven Models for Forecast River Flow
Milan Cisty, Juraj Bezak (Slovak University of Technology)

Portfolio Optimization Using Local Linear Regression Ensembles in Rapid Miner
Gábor Nagy, Tamás Henk, Gergő Barta (Budapest University of Technology and Economics)

Extensions

 

An Octave Extension for RapidMiner
Sylvain Marié (Schneider Electric)

 

Unstructured Data

 

Processing Data Streams with the RapidMiner Streams-Plugin
Christian Bockermann, Hendrik Blom (TU Dortmund)

Automated Creation of Corpuses for the Needs of Sentiment Analysis
Peter Koncz, Jan Paralic (Technical University of Kosice)

 

Demonstration: News from the Rapid-I Labs
Simon Fischer; Rapid-I

This short session demonstrates the latest developments from the Rapid-I lab and will let you how you can build powerful analysis processes and routines by using those RapidMiner tools.

Certification Exam
15:30 – 16:00
Coffee Break
Coffee Break
Coffee Break
16:00 – 18:00
Book Presentation and Game Show

Data Mining for the Masses: A New Textbook on Data Mining for Everyone
Matthew North (Washington & Jefferson College)

Matthew North presents his new book “Data Mining for the Masses” introducing data mining to a broader audience and making use of RapidMiner for practical data mining problems.

 

Game Show
Did you miss last years’ game show “Who wants to be a data miner?”? Use RapidMiner for problems it was never created for and beat the time and other contestants!

User Support

Get some Coffee for free – Writing Operators with RapidMiner Beans
Christian Bockermann, Hendrik Blom (TU Dortmund)

Meta-Modeling Execution Times of RapidMiner operators
Matija Piškorec, Matko Bošnjak, Tomislav Šmuc (Ruđer Bošković Institute)

Conference day ends at ca. 17:00.

19:30
Social Event (Conference Dinner)
Social Event (Visit of Bar District)

 

and you should have a look at https://rapid-i.com/rcomm2012f/index.php?option=com_content&view=article&id=65

Conference is in Budapest, Hungary,Europe.

( Disclaimer- Rapid Miner is an advertising sponsor of Decisionstats.com in case you didnot notice the two banner sized ads.)

 

Rapid Miner User Conference 2012

One of those cool conferences that is on my bucket list- this time in Hungary (That’s a nice place)

But I am especially interested in seeing how far Radoop has come along !

Disclaimer- Rapid Miner has been a Decisionstats.com sponsor  for many years. It is also a very cool software but I like the R Extension facility even more!

—————————————————————

and not very expensive too compared to other User Conferences in Europe!-

http://rcomm2012.org/index.php/registration/prices

Information about Registration

  • Early Bird registration until July 20th, 2012.
  • Normal registration from July 21st, 2012 until August 13th, 2012.
  • Latest registration from August 14th, 2012 until August 24th, 2012.
  • Students have to provide a valid Student ID during registration.
  • The Dinner is included in the All Days and in the Conference packages.
  • All prices below are net prices. Value added tax (VAT) has to be added if applicable.

Prices for Regular Visitors

Days and Event
Early Bird Rate
Normal Rate
Latest Registration
Tuesday

(Training / Development 1)

190 Euro 230 Euro 280 Euro
Wednesday + Thursday

(Conference)

290 Euro 350 Euro 420 Euro
Friday

(Training / Development 2 and Exam)

190 Euro 230 Euro 280 Euro
All Days

(Full Package)

610 Euro 740 Euro 900 Euro

Prices for Authors and Students

In case of students, please note that you will have to provide a valid student ID during registration.

Days and Event
Early Bird Rate
Normal Rate
Latest Registration
Tuesday

(Training / Development 1)

90 Euro 110 Euro 140 Euro
Wednesday + Thursday

(Conference)

140 Euro 170 Euro 210 Euro
Friday

(Training / Development 2 and Exam)

90 Euro 110 Euro 140 Euro
All Days

(Full Package)

290 Euro 350 Euro 450 Euro
Time
Slot
Tuesday
Training / Workshop 1
Wednesday
Conference 1
Thursday
Conference 2
Friday
Training / Workshop 2
09:00 – 10:30
Introductory Speech
Ingo Mierswa; Rapid-I 

Data Analysis

 

NeurophRM: Integration of the Neuroph framework into RapidMiner
Miloš Jovanović, Jelena Stojanović, Milan Vukićević, Vera Stojanović, Boris Delibašić (University of Belgrade)

To be announced (Invited Talk)
To be announced

 

Recommender Systems

 

Extending RapidMiner with Recommender Systems Algorithms
Matej Mihelčić, Nino Antulov-Fantulin, Matko Bošnjak, Tomislav Šmuc (Ruđer Bošković Institute)

Implementation of User Based Collaborative Filtering in RapidMiner
Sérgio Morais, Carlos Soares (Universidade do Porto)

Parallel Training / Workshop Session

Advanced Data Mining and Data Transformations

or

Development Workshop Part 2

10:30 – 12:30
Data Analysis

Nearest-Neighbor and Clustering based Anomaly Detection Algorithms for RapidMiner
Mennatallah Amer, Markus Goldstein (DFKI)

Customers’ LifeStyle Targeting on Big Data using Rapid Miner
Maksim Drobyshev (LifeStyle Marketing Ltd)

Robust GPGPU Plugin Development for RapidMiner
Andor Kovács, Zoltán Prekopcsák (Budapest University of Technology and Economics)

Extensions

Image Mining Extension – Year After
Radim Burget, Václav Uher, Jan Mašek (Brno University of Technology)

Incorporating R Plots into RapidMiner Reports
Peter Jeszenszky (University of Debrecen)

An Octave Extension for RapidMiner
Sylvain Marié (Schneider Electric)

12:30 – 13:30
Lunch
Lunch
Lunch
13:30 – 15:00
Parallel Training / Workshop Session

Basic Data Mining and Data Transformations

or

Development Workshop Part 1

Applications

Application of RapidMiner in Steel Industry Research and Development
Bengt-Henning Maas, Hakan Koc, Martin Bretschneider (Salzgitter Mannesmann Forschung)

A Comparison of Data-driven Models for Forecast River Flow
Milan Cisty, Juraj Bezak (Slovak University of Technology)

Portfolio Optimization Using Local Linear Regression Ensembles in Rapid Miner
Gábor Nagy, Tamás Henk, Gergő Barta (Budapest University of Technology and Economics)

Unstructured Data


Processing Data Streams with the RapidMiner Streams-Plugin
Christian Bockermann, Hendrik Blom (TU Dortmund)

Automated Creation of Corpuses for the Needs of Sentiment Analysis
Peter Koncz, Jan Paralic (Technical University of Kosice)

 

Demonstration

 

News from the Rapid-I Labs
Simon Fischer; Rapid-I

This short session demonstrates the latest developments from the Rapid-I lab and will let you how you can build powerful analysis processes and routines by using those RapidMiner tools.

Certification Exam
15:00 – 17:00
Book Presentation and Game Show

Data Mining for the Masses: A New Textbook on Data Mining for Everyone
Matthew North (Washington & Jefferson College)

Matthew North presents his new book “Data Mining for the Masses” introducing data mining to a broader audience and making use of RapidMiner for practical data mining problems.

 

Game Show
Did you miss last years’ game show “Who wants to be a data miner?”? Use RapidMiner for problems it was never created for and beat the time and other contestants!

User Support

Get some Coffee for free – Writing Operators with RapidMiner Beans
Christian Bockermann, Hendrik Blom (TU Dortmund)

Meta-Modeling Execution Times of RapidMiner operators
Matija Piškorec, Matko Bošnjak, Tomislav Šmuc (Ruđer Bošković Institute) 

19:00
Social Event (Conference Dinner)
Social Event (Visit of Bar District)

 

Training: Basic Data Mining and Data Transformations

This is a short introductory training course for users who are not yet familiar with RapidMiner or only have a few experiences with RapidMiner so far. The topics of this training session include

  • Basic Usage
    • User Interface
    • Creating and handling RapidMiner repositories
    • Starting a new RapidMiner project
    • Operators and processes
    • Loading data from flat files
    • Storing data, processes, and results
  • Predictive Models
    • Linear Regression
    • Naïve Bayes
    • Decision Trees
  • Basic Data Transformations
    • Changing names and roles
    • Handling missing values
    • Changing value types by discretization and dichotimization
    • Normalization and standardization
    • Filtering examples and attributes
  • Scoring and Model Evaluation
    • Applying models
    • Splitting data
    • Evaluation methods
    • Performance criteria
    • Visualizing Model Performance

 

Training: Advanced Data Mining and Data Transformations

This is a short introductory training course for users who already know some basic concepts of RapidMiner and data mining and have already used the software before, for example in the first training on Tuesday. The topics of this training session include

  • Advanced Data Handling
    • Sampling
    • Balancing data
    • Joins and Aggregations
    • Detection and removal of outliers
    • Dimensionality reduction
  • Control process execution
    • Remember process results
    • Recall process results
    • Loops
    • Using branches and conditions
    • Exception handling
    • Definition of macros
    • Usage of macros
    • Definition of log values
    • Clearing log tables
    • Transforming log tables to data

 

Development Workshop Part 1 and Part 2

Want to exchange ideas with the developers of RapidMiner? Or learn more tricks for developing own operators and extensions? During our development workshops on Tuesday and Friday, we will build small groups of developers each working on a small development project around RapidMiner. Beginners will get a comprehensive overview of the architecture of RapidMiner before making the first steps and learn how to write own operators. Advanced developers will form groups with our experienced developers, identify shortcomings of RapidMiner and develop a new extension which might be presented during the conference already. Unfinished work can be continued in the second workshop on Friday before results might be published on the Marketplace or can be taken home as a starting point for new custom operators.

New Plotters in Rapid Miner 5.2

I almost missed this because of my vacation and traveling

Rapid Miner has a tonne of new stuff (Statuary Ethics Declaration- Rapid Miner has been an advertising partner for Decisionstats – see the right margin)

see

http://rapid-i.com/component/option,com_myblog/Itemid,172/lang,en/

Great New Graphical Plotters

and some flashy work

and a great series of educational lectures

A Simple Explanation of Decision Tree Modeling based on Entropies

Link: http://www.simafore.com/blog/bid/94454/A-simple-explanation-of-how-entropy-fuels-a-decision-tree-model

Description of some of the basics of decision trees. Simple and hardly any math, I like the plots explaining the basic idea of the entropy as splitting criterion (although we actually calculate gain ratio differently than explained…)

Logistic Regression for Business Analytics using RapidMiner

Link: http://www.simafore.com/blog/bid/57924/Logistic-regression-for-business-analytics-using-RapidMiner-Part-2

Same as above, but this time for modeling with logistic regression.
Easy to read and covering all basic ideas together with some examples. If you are not familiar with the topic yet, part 1 (see below) might help.

Part 1 (Basics): http://www.simafore.com/blog/bid/57801/Logistic-regression-for-business-analytics-using-RapidMiner-Part-1

Deploy Model: http://www.simafore.com/blog/bid/82024/How-to-deploy-a-logistic-regression-model-using-RapidMiner

Advanced Information: http://www.simafore.com/blog/bid/99443/Understand-3-critical-steps-in-developing-logistic-regression-models

and lastly a new research project for collaborative data mining

http://www.e-lico.eu/

e-LICO Architecture and Components

The goal of the e-LICO project is to build a virtual laboratory for interdisciplinary collaborative research in data mining and data-intensive sciences. The proposed e-lab will comprise three layers: the e-science and data mining layers will form a generic research environment that can be adapted to different scientific domains by customizing the application layer.

  1. Drag a data set into one of the slots. It will be automatically detected as training data, test data or apply data, depending on whether it has a label or not.
  2. Select a goal. The most frequent one is probably “Predictive Modelling”. All goals have comments, so you see what they can be used for.
  3. Select “Fetch plans” and wait a bit to get a list of processes that solve your problem. Once the planning completes, select one of the processes (you can see a preview at the right) and run it. Alternatively, select multiple (selecting none means selecting all) and evaluate them on your data in a batch.

The assistant strives to generate processes that are compatible with your data. To do so, it performs a lot of clever operations, e.g., it automatically replaces missing values if missing values exist and this is required by the learning algorithm or performs a normalization when using a distance-based learner.

You can install the extension directly by using the Rapid-I Marketplace instead of the old update server. Just go to the preferences and enter http://rapidupdate.de:8180/UpdateServer as the update URL

Of course Rapid Miner has been of the most professional open source analytics company and they have been doing it for a long time now. I am particularly impressed by the product map (see below) and the graphical user interface.

http://rapid-i.com/content/view/186/191/lang,en/

Product Map

Just click on the products in the overview below in order to get more information about Rapid-I products.

 

Rapid-I Product Overview 

 

Interview Rapid-I -Ingo Mierswa and Simon Fischer

Here is an interview with Dr Ingo Mierswa , CEO of Rapid -I and Dr Simon Fischer, Head R&D. Rapid-I makes the very popular software Rapid Miner – perhaps one of the earliest leading open source software in business analytics and business intelligence. It is quite easy to use, deploy and with it’s extensions and innovations (including compatibility with R )has continued to grow tremendously through the years.

In an extensive interview Ingo and Simon talk about algorithms marketplace, extensions , big data analytics, hadoop, mobile computing and use of the graphical user interface in analytics.

Special Thanks to Nadja from Rapid I communication team for helping coordinate this interview.( Statuary Blogging Disclosure- Rapid I is a marketing partner with Decisionstats as per the terms in https://decisionstats.com/privacy-3/)

Ajay- Describe your background in science. What are the key lessons that you have learnt while as scientific researcher and what advice would you give to new students today.

Ingo: My time as researcher really was a great experience which has influenced me a lot. I have worked at the AI lab of Prof. Dr. Katharina Morik, one of the persons who brought machine learning and data mining to Europe. Katharina always believed in what we are doing, encouraged us and gave us the space for trying out new things. Funnily enough, I never managed to use my own scientific results in any real-life project so far but I consider this as a quite common gap between science and the “real world”. At Rapid-I, however, we are still heavily connected to the scientific world and try to combine the best of both worlds: solving existing problems with leading-edge technologies.

Simon: In fact, during my academic career I have not worked in the field of data mining at all. I worked on a field some of my colleagues would probably even consider boring, and that is theoretical computer science. To be precise, my research was in the intersection of game theory and network theory. During that time, I have learnt a lot of exciting things, none of which had any business use. Still, I consider that a very valuable experience. When we at Rapid-I hire people coming to us right after graduating, I don’t care whether they know the latest technology with a fancy three-letter acronym – that will be forgotten more quickly than it came. What matters is the way you approach new problems and challenges. And that is also my recommendation to new students: work on whatever you like, as long as you are passionate about it and it brings you forward.

Ajay-  How is the Rapid Miner Extensions marketplace moving along. Do you think there is a scope for people to say create algorithms in a platform like R , and then offer that algorithm as an app for sale just like iTunes or Android apps.

 Simon: Well, of course it is not going to be exactly like iTunes or Android apps are, because of the more business-orientated character. But in fact there is a scope for that, yes. We have talked to several developers, e.g., at our user conference RCOMM, and several people would be interested in such an opportunity. Companies using data mining software need supported software packages, not just something they downloaded from some anonymous server, and that is only possible through a platform like the new Marketplace. Besides that, the marketplace will not only host commercial extensions. It is also meant to be a platform for all the developers that want to publish their extensions to a broader community and make them accessible in a comfortable way. Of course they could just place them on their personal Web pages, but who would find them there? From the Marketplace, they are installable with a single click.

Ingo: What I like most about the new Rapid-I Marketplace is the fact that people can now get something back for their efforts. Developing a new algorithm is a lot of work, in some cases even more that developing a nice app for your mobile phone. It is completely accepted that people buy apps from a store for a couple of Dollars and I foresee the same for sharing and selling algorithms instead of apps. Right now, people can already share algorithms and extensions for free, one of the next versions will also support selling of those contributions. Let’s see what’s happening next, maybe we will add the option to sell complete RapidMiner workflows or even some data pools…

Ajay- What are the recent features in Rapid Miner that support cloud computing, mobile computing and tablets. How do you think the landscape for Big Data (over 1 Tb ) is changing and how is Rapid Miner adapting to it.

Simon: These are areas we are very active in. For instance, we have an In-Database-Mining Extension that allows the user to run their modelling algorithms directly inside the database, without ever loading the data into memory. Using analytic databases like Vectorwise or Infobright, this technology can really boost performance. Our data mining server, RapidAnalytics, already offers functionality to send analysis processes into the cloud. In addition to that, we are currently preparing a research project dealing with data mining in the cloud. A second project is targeted towards the other aspect you mention: the use of mobile devices. This is certainly a growing market, of course not for designing and running analyses, but for inspecting reports and results. But even that is tricky: When you have a large screen you can display fancy and comprehensive interactive dashboards with drill downs and the like. On a mobile device, that does not work, so you must bring your reports and visualizations very much to the point. And this is precisely what data mining can do – and what is hard to do for classical BI.

Ingo: Then there is Radoop, which you may have heard of. It uses the Apache Hadoop framework for large-scale distributed computing to execute RapidMiner processes in the cloud. Radoop has been presented at this year’s RCOMM and people are really excited about the combination of RapidMiner with Hadoop and the scalability this brings.

 Ajay- Describe the Rapid Miner analytics certification program and what steps are you taking to partner with academic universities.

Ingo: The Rapid-I Certification Program was created to recognize professional users of RapidMiner or RapidAnalytics. The idea is that certified users have demonstrated a deep understanding of the data analysis software solutions provided by Rapid-I and how they are used in data analysis projects. Taking part in the Rapid-I Certification Program offers a lot of benefits for IT professionals as well as for employers: professionals can demonstrate their skills and employers can make sure that they hire qualified professionals. We started our certification program only about 6 months ago and until now about 100 professionals have been certified so far.

Simon: During our annual user conference, the RCOMM, we have plenty of opportunities to talk to people from academia. We’re also present at other conferences, e.g. at ECML/PKDD, and we are sponsoring data mining challenges and grants. We maintain strong ties with several universities all over Europe and the world, which is something that I would not want to miss. We are also cooperating with institutes like the ITB in Dublin during their training programmes, e.g. by giving lectures, etc. Also, we are leading or participating in several national or EU-funded research projects, so we are still close to academia. And we offer an academic discount on all our products 🙂

Ajay- Describe the global efforts in making Rapid Miner a truly international software including spread of developers, clients and employees.

Simon: Our clients already are very international. We have a partner network in America, Asia, and Australia, and, while I am responding to these questions, we have a training course in the US. Developers working on the core of RapidMiner and RapidAnalytics, however, are likely to stay in Germany for the foreseeable future. We need specialists for that, and it would be pointless to spread the development team over the globe. That is also owed to the agile philosophy that we are following.

Ingo: Simon is right, Rapid-I already is acting on an international level. Rapid-I now has more than 300 customers from 39 countries in the world which is a great result for a young company like ours. We are of course very strong in Germany and also the rest of Europe, but also concentrate on more countries by means of our very successful partner network. Rapid-I continues to build this partner network and to recruit dynamic and knowledgeable partners and in the future. However, extending and acting globally is definitely part of our strategic roadmap.

Biography

Dr. Ingo Mierswa is working as Chief Executive Officer (CEO) of Rapid-I. He has several years of experience in project management, human resources management, consulting, and leadership including eight years of coordinating and leading the multi-national RapidMiner developer team with about 30 developers and contributors world-wide. He wrote his Phd titled “Non-Convex and Multi-Objective Optimization for Numerical Feature Engineering and Data Mining” at the University of Dortmund under the supervision of Prof. Morik.

Dr. Simon Fischer is heading the research & development at Rapid-I. His interests include game theory and networks, the theory of evolutionary algorithms (e.g. on the Ising model), and theoretical and practical aspects of data mining. He wrote his PhD in Aachen where he worked in the project “Design and Analysis of Self-Regulating Protocols for Spectrum Assignment” within the excellence cluster UMIC. Before, he was working on the vtraffic project within the DFG Programme 1126 “Algorithms for large and complex networks”.

http://rapid-i.com/content/view/181/190/ tells you more on the various types of Rapid Miner licensing for enterprise, individual and developer versions.

(Note from Ajay- to receive an early edition invite to Radoop, click here http://radoop.eu/z1sxe)

 

Machine Learning Contest

New Contest at http://www.ecmlpkdd2011.org/dcOverview.php

 

 

Discovery Challenge Overview

Organization | Overview | Task and DatasetsTimeline

 

General description: tasks and dataset

VideoLectures.net is a free and open access multimedia repository of video lectures, mainly of research and educational character. The lectures are given by distinguished scholars and scientists at the most important and prominent events like conferences, summer schools, workshops and science promotional events from many fields of Science. The portal is aimed at promoting science, exchanging ideas and fostering knowledge sharing by providing high quality didactic contents not only to the scientific community but also to the general public. All lectures, accompanying documents, information and links are systematically selected and classified through the editorial process taking into account also users’ comments.

The ECML-PKDD 2011 Discovery Challenge is organized in order to improve the website’s current recommender system. The challenge consists of two main tasks and a “side-by” contest. The provided data is for both of the tasks, and it is up to the contestants how it will be used for learning (building up) a recommender.

Due to the nature of the problem, each of the tasks has its own merit: task 1 simulates new-user and new- item recommendation (cold-start mode), task 2 simulates clickstream based recommendation (normal mode). Continue reading “Machine Learning Contest”

RapidMiner launches extensions marketplace

For some time now, I had been hoping for a place where new package or algorithm developers get at least a fraction of the money that iPad or iPhone application developers get. Rapid Miner has taken the lead in establishing a marketplace for extensions. Is there going to be paid extensions as well- I hope so!!

This probably makes it the first “app” marketplace in open source and the second app marketplace in analytics after salesforce.com

It is hard work to think of new algols, and some of them can really be usefull.

Can we hope for #rstats marketplace where people downloading say ggplot3.0 atleast get a prompt to donate 99 cents per download to Hadley Wickham’s Amazon wishlist. http://www.amazon.com/gp/registry/1Y65N3VFA613B

Do you think it is okay to pay 99 cents per iTunes song, but not pay a cent for open source software.

I dont know- but I am just a capitalist born in a country that was socialist for the first 13 years of my life. Congratulations once again to Rapid Miner for innovating and leading the way.

http://rapid-i.com/component/option,com_myblog/show,Rapid-I-Marketplace-Launched.html/Itemid,172

RapidMinerMarketplaceExtensions 30 May 2011
Rapid-I Marketplace Launched by Simon Fischer

Over the years, many of you have been developing new RapidMiner Extensions dedicated to a broad set of topics. Whereas these extensions are easy to install in RapidMiner – just download and place them in the plugins folder – the hard part is to find them in the vastness that is the Internet. Extensions made by ourselves at Rapid-I, on the other hand,  are distributed by the update server making them searchable and installable directly inside RapidMiner.

We thought that this was a bit unfair, so we decieded to open up the update server to the public, and not only this, we even gave it a new look and name. The Rapid-I Marketplace is available in beta mode at http://rapidupdate.de:8180/ . You can use the Web interface to browse, comment, and rate the extensions, and you can use the update functionality in RapidMiner by going to the preferences and entering http://rapidupdate.de:8180/UpdateServer/ as the update server URL. (Once the beta test is complete, we will change the port back to 80 so we won’t have any firewall problems.)

As an Extension developer, just register with the Marketplace and drop me an email (fischer at rapid-i dot com) so I can give you permissions to upload your own extension. Upload is simple provided you use the standard RapidMiner Extension build process and will boost visibility of your extension.

Looking forward to see many new extensions there soon!

Disclaimer- Decisionstats is a partner of Rapid Miner. I have been liking the software for a long long time, and recently agreed to partner with them just like I did with KXEN some years back, and with Predictive AnalyticsConference, and Aster Data until last year.

I still think Rapid Miner is a very very good software,and a globally created software after SAP.

Here is the actual marketplace

http://rapidupdate.de:8180/UpdateServer/faces/index.xhtml

Welcome to the Rapid-I Marketplace Public Beta Test

The Rapid-I Marketplace will soon replace the RapidMiner update server. Using this marketplace, you can share your RapidMiner extensions and make them available for download by the community of RapidMiner users. Currently, we are beta testing this server. If you want to use this server in RapidMiner, you must go to the preferences and enter http://rapidupdate.de:8180/UpdateServer for the update url. After the beta test, we will change the port back to 80, which is currently occupied by the old update server. You can test the marketplace as a user (downloading extensions) and as an Extension developer. If you want to publish your extension here, please let us know via the contact form.

Hot Downloads
«« « 1 2 3 » »»
[Icon]The Image Processing Extension provides operators for handling image data. You can extract attributes describing colour and texture in the image, you can make several transformation of a image data which allows you to perform segmentation and detection of suspicious areas in image data.The extension provides many of image transformation and extraction operators ranging from Wavelet Decomposition, Hough Circle to Block Difference of Inverse probabilities.

[Icon]RapidMiner is unquestionably the world-leading open-source system for data mining. It is available as a stand-alone application for data analysis and as a data mining engine for the integration into own products. Thousands of applications of RapidMiner in more than 40 countries give their users a competitive edge.

  • Data IntegrationAnalytical ETLData Analysis, and Reporting in one single suite
  • Powerful but intuitive graphical user interface for the design of analysis processes
  • Repositories for process, data and meta data handling
  • Only solution with meta data transformation: forget trial and error and inspect results already during design time
  • Only solution which supports on-the-fly error recognition and quick fixes
  • Complete and flexible: Hundreds of data loading, data transformation, data modeling, and data visualization methods
[Icon]All modeling methods and attribute evaluation methods from the Weka machine learning library are available within RapidMiner. After installing this extension you will get access to about 100 additional modelling schemes including additional decision trees, rule learners and regression estimators.This extension combines two of the most widely used open source data mining solutions. By installing it, you can extend RapidMiner to everything what is possible with Weka while keeping the full analysis, preprocessing, and visualization power of RapidMiner.

[Icon]Finally, the two most widely used data analysis solutions – RapidMiner and R – are connected. Arbitrary R models and scripts can now be directly integrated into the RapidMiner analysis processes. The new R perspective offers the known R console together with the great plotting facilities of R. All variables and R scripts can be organized in the RapidMiner Repository.A directly included online help and multi-line editing makes the creation of R scripts much more comfortable.