1. Justin Sun Boston DataCon September 14, 2014

2. Overview Why Use Orange? Classification Tree Example Project History Architecture Widgets Demo Resources

3. 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

4. Classification Tree Scheme

5. 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

6. High-level Architecture Algorithms written in C++ Python integration layer (Python 2.7) Orange Canvas – Visual programming

7. 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

9. Scheme Widgets

15. Demo Classification example Evaluation

16. 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

17. Thank You!