Orange Canvas A Visual Programming Environment for Data Mining

1. Orange CanvasA Visual Programming Environment for Data Mining 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++. • 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%29

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

7. Installation • Download full package installer from 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/ • Tutorials: http://www.biolab.si/janez/kyoto/ • Interactive Network Analysis with Orange http://www.jstatsoft.org/v53/i06 • Orange Whitepaper with scripting examples http://www.celta.paris-sorbonne.fr/anasem/papers/miscelanea/InteractiveDataMining.pdf

17. Thank You!