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Justin Sun Boston DataCon September 14, 2014
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Overview Why Use Orange? Classification Tree Example Project History Architecture Widgets Demo Resources
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Why Use Orange? Free and open source No programming needed Visual programming Interactive Easy to Use – Encourages Experimentation Data Visualizations Machine Learning Algorithms Add-ons for Bioinformatics Network Analysis Text Analytics
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Classification Tree Scheme
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History 1996 – University of Ljubljana and Jožef Stefan Institute started development of ML*, a machine learning framework in C++.University of LjubljanaJožef Stefan Institute 1997 – Python integration layer 2003 – GUI based on PyQt 2013 – Orange Canvas 2.7 released – Major GUI redesign. Source: http://en.wikipedia.org/wiki/Orange_%28software%29http://en.wikipedia.org/wiki/Orange_%28software%29
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High-level Architecture Algorithms written in C++ Python integration layer (Python 2.7) Orange Canvas – Visual programming
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Installation Download full package installer from http://orange.biolab.si/ http://orange.biolab.si/ Run installer Requires Python 2.7 Includes NumPy, SciPy, PyQt, other required libraries After installing, double-click on the Orange Canvas icon
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Scheme Widgets
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Demo Classification example Evaluation
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Resources Orange Website: http://orange.biolab.si/ http://orange.biolab.si/ Tutorials: http://www.biolab.si/janez/kyoto/ http://www.biolab.si/janez/kyoto/ Interactive Network Analysis with Orange http://www.jstatsoft.org/v53/i06 http://www.jstatsoft.org/v53/i06 Orange Whitepaper with scripting examples http://www.celta.paris- sorbonne.fr/anasem/papers/miscelanea/InteractiveDataMining.pdf http://www.celta.paris- sorbonne.fr/anasem/papers/miscelanea/InteractiveDataMining.pdf
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Thank You!
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