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Information filtering and selection[Information Selection and Prototype-based Rules]

Information Selection and Prototype-based Rules. A way to mine, understand and look into big data. Information filtering and selection. Information filtering and selection. Nowadays data mining techniques become more and more popular, however building data driven models we face several independent problems:. Model accuracy - the model should be as accurate as possible, preserving good generalization. Accuracy can be improved by rejecting outliers from the data. The big data challenge can be also solved b...

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Information filtering and selection[Information Selection and Prototype-based Rules] | prules.org Reviews

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Information Selection and Prototype-based Rules. A way to mine, understand and look into big data. Information filtering and selection. Information filtering and selection. Nowadays data mining techniques become more and more popular, however building data driven models we face several independent problems:. Model accuracy - the model should be as accurate as possible, preserving good generalization. Accuracy can be improved by rejecting outliers from the data. The big data challenge can be also solved b...

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research,publications,download,team,sidebar,prototype selection,feature selection,related projects,ispr,myspider,infosel,spreadsheet link,toolbox,back to top,why prototype based rules,prototype based rules,or shortly p rules,in general p rules,starttxt

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Information filtering and selection[Information Selection and Prototype-based Rules] | prules.org Reviews

https://prules.org

Information Selection and Prototype-based Rules. A way to mine, understand and look into big data. Information filtering and selection. Information filtering and selection. Nowadays data mining techniques become more and more popular, however building data driven models we face several independent problems:. Model accuracy - the model should be as accurate as possible, preserving good generalization. Accuracy can be improved by rejecting outliers from the data. The big data challenge can be also solved b...

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prules.org

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Information filtering and selection[Information Selection and Prototype-based Rules]

http://www.prules.org/doku.php/start

Information Selection and Prototype-based Rules. A way to mine, understand and look into big data. Information filtering and selection. Information filtering and selection. Nowadays data mining techniques become more and more popular, however building data driven models we face several independent problems:. Model accuracy - the model should be as accurate as possible, preserving good generalization. Accuracy can be improved by rejecting outliers from the data. The big data challenge can be also solved b...

2

MySpider[Information Selection and Prototype-based Rules]

http://www.prules.org/doku.php/download:myspider

Information Selection and Prototype-based Rules. A way to mine, understand and look into big data. Is an extension to Spider. Is an advanced data mining. Toolbox released on GNU. V3 licence. It is object oriented set of classes which allows to build complex data analysis flow. It includes tools for data preprocessing, large set of classification algorithms, bat also algorithms for regression, data clustering, feature selection, model selection etc. Because. MySpider can be obtained from Spider. Myparam -...

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download[Information Selection and Prototype-based Rules]

http://www.prules.org/doku.php/download

Information Selection and Prototype-based Rules. A way to mine, understand and look into big data. Go to this page. Here you can get access to the software developed by our group. We have developed three big packages:. Infosel (developed by Jacek Biesiada and Adam Kachel). But also some smaller packages:. Go to this page. Last modified: 2015/05/08 23:58 (external edit).

4

Publications[Information Selection and Prototype-based Rules]

http://www.prules.org/doku.php/publications

Information Selection and Prototype-based Rules. A way to mine, understand and look into big data. Below is a list of our publications related to the prototype selection problem. Total numer of publications: 22. M Blachnik, M. Kordos, T. Wieczorek, S. Golak Selecting Representative Prototypes for Prediction the Oxygen Activity in Electric Arc Furnace. M Blachnik, M. Kordos Computational Complexity Reduction and Interpretability Improvement of Distance-based Decision Trees. 7208 pp. 288-297. 2012. M Blach...

5

ISPR[Information Selection and Prototype-based Rules]

http://www.prules.org/doku.php/download:ispr

Information Selection and Prototype-based Rules. A way to mine, understand and look into big data. We develop an extension to RapidMiner. Which can be used for instance selection, but also for mining large datasets, to shrink them to be acceptable by common data mining algorithms. Instance Selection and Prototype-Based Rule (ISPR) plugin can be installed directly from RapidMiner marketplace by selecting in menu. Help Updates and Extensions. Checkout and update commands has public access.

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kordos.com

Mirosław Kordos: .NET and AI

http://www.kordos.com/resume.html

SQL Server 2008 Database Developer. MCPD - Microsoft Certified Professional Developer. MCTS NET 2.0. PhD in Computer Engineering. CAE - Certificate in Advanced English (grade A). Postgraduate Studies in Management. MBA - Master of Business Administration. Artificial intelligence - neural networks and data selection. Software development in .NET. Education and Job History. 2011: MBA (Master of Business Administration). 2005: PhD in Computer Engineering. 1994: MSc in Electrical Engineering. Lecture Notes i...

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Information filtering and selection[Information Selection and Prototype-based Rules]

Information Selection and Prototype-based Rules. A way to mine, understand and look into big data. Information filtering and selection. Information filtering and selection. Nowadays data mining techniques become more and more popular, however building data driven models we face several independent problems:. Model accuracy - the model should be as accurate as possible, preserving good generalization. Accuracy can be improved by rejecting outliers from the data. The big data challenge can be also solved b...

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