preload
Mar 16

KnowledgeMiner – Copper

Make Better Decisions.

64-bit Parallel Self-organizing Predictive Modeling from Data: Mine. Extract. Predict. Identify. Simulate.
Also: Get a 25% discount when upgrading to Silver or Gold Edition during this ZOT! (Use code 3XCG-TZRE-76HP)



Normally: $105.00

ZOT Price: $25.00

Click to macZOT! Download Trial




 

Make Better Decisions Based on Relevant Data.

 

"I believe that tools like this are definitely the start of something very big in getting a handle on mountains of information." — Douglas, Dartmouth Medical School

 

Do you know the value of your data? Find unknown relevant relationships in your scientific, business or personal data easily by using outstanding self-organizing knowledge mining methods for prediction, classification, identification or simulation tasks in various fields.

 

KnowledgeMiner comes with documentation, extra literature, sample data and models such as:

  • World Oil Price prediction and simulation till 2025
  • Monthly Global Temperature predictions and What Drives Global Warming
  • Reproductive Toxicity prediction of chemicals to help you getting started with your data.

KnowledgeMiner Changes the Game for Small Businesses.

 

KnowledgeMiner is a professional, yet user friendly tool for building predictive models from noisy data autonomously. Whether applied to sales predictions, financial and resource planning, engineering problems, climate change, health or life sciences related questions, or mining collections of data from government agencies – KnowledgeMiner opens up a wealth of new possibilities to individuals, small business owners, and scientists that were previously available only to large entities that could afford expensive data mining applications.

 

Visit KnowledgeMiner to get all the details of the content above.

 

Why do I need a model?

Clearly, we are facing an ever-widening spectrum of complex problems, which require analysis and action. However, the means and adequate models for understanding, simulating, and predicting such problems often do not exist. This is particularly the case in many real-world, socio-economic, eco-economic, ecological, biological, and energy challenges. To fill this knowledge gap, new, inductive learning, self-organizing modeling methods have to be applied, which can help reveal the missing, implicit relationships in complex systems in an adaptive, fast, reliable, and objective way.

 

The efficiency and reliability of this self-organizing modeling approach has been proven in the past decades by numerous practical applications. More recent ones include the modeling and prediction of harmful health and environmental effects of chemicals such as carcinogenicity, mutagenicity or bioaccumulation for regulatory purposes and consumer safety to minimize animal tests, which was done in cooperation with the Istituto Mario Negri, Italy, the U.S. Environmental Protection Agency, the UK Food and Environment Research Agency, and others. (VEGA project)

 

Another example that shows the power and value of KnowledgeMiner is an ex ante forecast of monthly global mean temperatures until November 2017, which is based on models that were developed back in May 2010 and which is available for live actual vs predicted comparison.

 

 

Feature Highlights:

  • Brings high-performance Personal Knowledge Mining to users with unprecedented ease of model building and deployment – takes full advantage of the computing power of your Mac.
  • Hides all complex processes of knowledge extraction, model development, dimension reduction, variables selection, noise filtering, and model validation from the user.
  • Self-organizes linear or nonlinear, static or dynamic regression models and model ensembles – generates the equation that describes the data.
  • Checks if, and the extent to which, the developed model reflects a valid relationship or if it just models noise – employs advanced validation methods based on higher-dimensional modeling
  • Live Prediction Validation technology – for the first time, gives direct information about model stability for the given input values
  • Generated analytical models can be used for Status Quo or What-If prediction, analysis, simulation, or optimization problems
  • Optionally, it implements models and model ensembles in Excel – model export requires Microsoft Excel for Mac 2011 or 2008

Language Support:

  • English, Spanish, and German

 

Quotes from users:

"I like KnowledgeMiner because its algorithm does not make any assumtions on the underlying data; well, at least not during the initial model-building phase. I also like the fact that it generates sets of equations that the user can review with detailed understanding of the interactions and dependencies of each variable. Also, the algorithm(s) behave surprising well under extreme conditions for certain complex dynamical systems. Congratulations for your excellent work." — Alexis Pobedonostzeff, Pfizer Inc., Director, Health Care Issues Analysis & Management

 

"I have purchased your program KnowledgeMiner and have had some time to use it. My research is in artificial intelligence applications in clinical medicine at the University of Western Ontario in London, Canada. I have so far used backward error propagation and probalistic ANNs for outcomes based research. I also have some experience with fuzzy decision theory and expert systems. Your program looks interesting and has some advantages over my current modelling software. … I wish to congratulate you on your very promising software." — Wayne, Associate Professor of Medicine, Division of Cardiology, University of Western Ontario, London, Canada

 

"Lovely maths and algorithms. Nice and simple product. Feel that it can significantly assist me. Looking forward to understanding it better to put it to real use." — Dr. Conrad Mackenzie, Australia

 

"KnowledgeMiner is the most advanced implementation of the GMDH approach now. It uses the inductive method, which is different from deductive techniques used commonly for modeling on principle. Many important successful results were received using this tool recently. They show the advantage of it over analogous well-known software." — Prof. Alexey G. Ivakhnenko, author of the self-organizing modeling approach (GMDH)


About Us.

 

Leading Knowledge Mining Technologies for the Mac.

KnowledgeMiner Software was founded by Frank Lemke in 1993 in Berlin, Germany. The company is active in research, development, consulting, and application of unique self-organizing modeling and knowledge discovery technologies. It developed the KnowledgeMiner® software package, a distinguished commercial self-organizing modeling and knowledge extraction tool for the Mac. The software implements an outstanding set of parallel algorithms for modeling, validation, and workflow processing of complex systems to allow knowledge extraction from noisy real-world data in a most objective, automated, and fast way. The company developed and implemented a number of original technologies for validation of inductively built data mining models including new approaches for application domain definition and identification, cost-sensitive and ensemble modeling with per-sample prediction uncertainty, and self-organizing knowledge extraction from high-dimensional variables space of noisy data. 
It is also the developer of former KnowledgeMiner Classic and KnowledgeMiner (yX) for Excel software packages.
  KnowledgeMiner Software has been doing consulting in model development and prediction of toxicological and eco-toxicological hazards and risks of chemical compounds from experimental data for regulatory purposes within REACH and participated in three international research projects funded by the European Commission related to QSAR modeling and model evaluation. Other fields of activity have been climate change related modeling and prediction problems, sales and demand predictions, macro- and micro-economic modeling problems like national economy and balance sheet prediction, energy consumption analysis and prediction, medical diagnosis of diseases, and wastewater reuse problems.

KnowledgeMiner is supporting the FuturICT project, a major international public effort on modeling, understanding, and simulating our complex, global, interconnected socio-eco-economic world.


 


 

KnowledgeMiner® is being used by:
 

NASA, Boeing, MIT, Columbia, Notre Dame, Mobil Oil, Pfizer, Merck, Dean & Company, and many other corporations, universities, research institutes and individuals around the world.

KnowledgeMiner Software contributed to a number of international research projects, for example:

Caesar Project VEGA Platform FuturICT

 



System Requirements:

* OS X 10.7 Lion or higher?

* 64-bit CPU ?

* Minimum screen resolution of 1280 x 768 pixel? Do* For Excel support, Excel versions 2011 or 2008

7 Responses to “KnowledgeMiner – Copper”

  1. jpmckeown Says:

    I’m struggling to understand the differences between this Copper version (link comparing with Gold and Silver is broken), and the yX Excel version of KnowledgeMiner.
    regards, Dr J P McKeown

  2. knowledgeminer Says:

    The link on this page is working now. Sorry for the trouble.
    KnowledgeMiner (yX) for Excel is the predecessor of this new KnowledgeMiner. In this new KnowledgeMiner Copper you always build model ensembles for expressing uncertainty and also export them to Excel, you store every generated model in a model base, for the first time in any data mining product you use Live Prediction Validation that expresses model robustness for any new input values (i.e., if the model is working reliably for this specific input values, if it’s in its applicability domain), and others.

  3. dafuller Says:

    I’ve the previous version of Knowledgeminer… Are there any opportunities for a similarly massive discount of the Über version Gold :-)

  4. knowledgeminer Says:

    :-) OK, contact me which version you have.

  5. gferraiolo Says:

    This is very interesting but it’s hard to understand without some more documentation. Is the Copper version actually useful? I’m not familiar with this technology so I can’t judge based on the parameters listed. Is it possible to give some examples of analyses that can and cannot be accomplished with the Copper version? Thanks in advance.

  6. sensano Says:

    You claim KnowledgeMiner is for small businesses also. I hope so, but I am new to this field and cannot find any examples for small business use cases on your site or this page.
    Are there any more examples available which are business, (software) engineering or even personal area related?
    Is support available to get interested noobs (like me) going with the first setups?

  7. knowledgeminer Says:

    I agree about the documentation. We will add more over time.
    The Copper version can be used already for many classification and identification problems, for instance. The oil price example included in the package which consists also of prediction of world population, oil consumption and production, the computer system activity example or the housing value example (all included in the package) can be solved with Copper. Also sales prediction or quite some people try to use it for financial/stock market prediction. Potentially every problem that is described by (observed) data. These data can be noisy, disturbed. KM still works due to noise filtering. If you look around you find a wealth of data and data sources which allow to look at so many problems. Today, almost all big companies use data mining in some way for mining customer data for different purposes. KnowledgeMiner never followed this path, but this is what happens in industry and even small companies could do CRM with KM if they like…
    And yes, if somebody comes up with a small question about KM we usually give online support.