Orange Canvas A Visual Programming Environment for Data Mining

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!

Orange Canvas A Visual Programming Environment for Data Mining

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Transcript of Orange Canvas A Visual Programming Environment for Data Mining

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