Orange CanvasA Visual Programming Environment for Data
MiningJustin Sun
Boston DataConSeptember 14, 2014
OverviewWhy Use Orange?Classification Tree ExampleProject HistoryArchitectureWidgetsDemoResources
Why Use Orange?Free and open sourceNo programming needed
Visual programmingInteractive
Easy to Use – Encourages ExperimentationData VisualizationsMachine Learning Algorithms
Add-ons forBioinformaticsNetwork AnalysisText Analytics
Classification Tree Scheme
History1996 – University of Ljubljana and Jožef
Stefan Institute started development of ML*, a machine learning framework in C++.
1997 – Python integration layer2003 – GUI based on PyQt2013 – Orange Canvas 2.7 released – Major
GUI redesign.
Source: http://en.wikipedia.org/wiki/Orange_%28software%29
High-level Architecture
Algorithms written in C++
Python integration layer (Python 2.7)
Orange Canvas – Visual programming
InstallationDownload full package installer from
http://orange.biolab.si/Run installer
Requires Python 2.7Includes NumPy, SciPy, PyQt, other required
librariesAfter installing, double-click on the Orange
Canvas icon
Scheme
Widgets
DemoClassification exampleEvaluation
ResourcesOrange 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
Thank You!
