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François Rioult, 03/02/2011 18:49

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h1. Documentation
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KDAriane is a set of operators for data mining and machine learning, and a set of scenarios (supervised classification, missing values completion, strong emerging pattern mining, etc.). It uses Ariane as a graphical platform for designing the data streams.
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h2. Installation
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* [[Prerequisite]]
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* [[KDAriane]] 
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h2. Tutorial
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You can read the document [[Data preparation]] for a first contact with @KDAriane@.
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h2. How is Ariane working?
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Ariane is a graphical platform for designing image processing streams. Ariane works with graphical operators, and allows to build loops and while.
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"Go to the Aiane dedicated site":http://www.greyc.ensicaen.fr/~regis/Ariane/ for a full documentation about Ariane.
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h2. How is KDAriane working?
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KDAriane is provided with basic components for executing shell scripts. When an operator is executed, Ariane launches the script with giving the following arguments:
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<pre>
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script.sh parameter-1 parameter-2 ... parameter-p input-1 input-2 ... input-i output-1 output-2 ... output-o
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</pre>
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See [[Special operators for shell scripting]] for more details.
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h2. Operators
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The operator are divided in two categories: 
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* [[KDD operators]] are special components for calling Weka components or RapidMiner processes.
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* [[Shell operators]] that directly execute the commands entered by Ariane. 
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h2. Pattern mining prototypes
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* [[music-dfs]] : mining patterns under various constraints
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* [[mtminer]] : levelwise minimal transversals of hypergraph
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h2. Scenarios
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KDAriane provides some examples of KDD realized through Ariane:
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* [[Data preparation]] : a first scenario for the binarization of CSV data.
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* pattern mining and complexity visualization
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* supervised classification with association rules
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* experiences about perturbation on training and test file with Weka classifiers and RapidMiner processes.
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h2. Routines
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Routines are complex streams that Ariane allows you to share.
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* [[shell routines]]
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* [[KDD routines]]
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h2. Appendix
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h3. Utilities
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* [[score]] :
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* [[complement]] :
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* [[dictionary]] :
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* [[segmentation]] :
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h3. References