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Data Mining and Predictive Analytics Toolkit December 2013, Jakub Miarka, University of Leeds.

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Presentation on theme: "Data Mining and Predictive Analytics Toolkit December 2013, Jakub Miarka, University of Leeds."— Presentation transcript:

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2 Data Mining and Predictive Analytics Toolkit December 2013, Jakub Miarka, University of Leeds

3 RAPIDMINER Formerly called YALE (Yet Another Language Environment) Environment for machine learning, data and text mining, predictive and business analytics Started in 2001 at the Artificial Intelligence Unit of the Dortmund University of Technology, Germany 2006 – Rapid-I founded AGPL open source license until November 2013 Profitable company, growing organically 3 millions downloads / 200,000 users One of the leaders in the predictive analytics

4 USAGE GUI for building data mining/analytics workflows Highly scalable predictive analytics application Learning schemes and attribute evaluators from WEKA Integrates with popular enterprise data sources (60+, incl. SAP) Supports both structured and unstructured data Typically used for: customer segmentation loyalty and retention analysis credit ratings asset maintenance resource planning

5 A pie chart showing aggregated information Multiple results displayed simultaneously

6 BENEFITS No programming skills needed and easy to use (GUI, drag & drop…) analytical methods 120+ models incl. decision trees and dozens of visualisations available Powerful and scalable Flexible, scriptable, supports plugins and extensions Provides a GUI to design an analytical pipeline (the "operator tree") which defines the analytical processes the user wishes to apply to the data Other applications can use the engine through API

7 POPULARITY Suitable for individuals and large enterprises as well Some of the customers: PayPal PepsiCo eBay Volkswagen Lufthansa … and many more

8 NOVEMBER 2013 AND FUTURE $5 millions investment Rebranded from Rapid-I to RapidMiner Core stays open source but new commercial packages introduced When a new version is published, previous ones become free In future, increased focus on Big Data and self-service-style interface for less technical and more business-focused users A vision to become the industry standard for predictive analytics

9 REFERENCES


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