Documentation » Historique » Révision 35
Révision 34 (François Rioult, 18/11/2012 17:29) → Révision 35/37 (François Rioult, 06/12/2012 20:57)
h1. Documentation
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.
h2. Demonstration
You can watch the [[short demonstration of KDAriane]].
h2. Installation
* [[Prerequisite]]
* [[KDAriane]]
h2. Tutorial
You can read the document [[Data preparation]] for a first contact with @KDAriane@.
h2. Scenarios
In the @sample@ folder, @KDAriane@ provides some examples of KDD scenarios:
* [[Data preparation]]: a first scenario for the binarization of CSV data.
* [[Data mining complexity]]: pattern mining and complexity visualization
* [[CMAR]]: supervised classification with association rules [1]
h2. How is Ariane working?
Ariane is a graphical platform for designing image processing streams. Ariane works with graphical operators, and allows to build loops and while.
"Go to the Aiane dedicated site":http://www.greyc.ensicaen.fr/~regis/Ariane/ for a full documentation about Ariane.
KDAriane is provided with basic components for executing shell scripts. When an operator is executed, Ariane launches the script with giving the following arguments:
<pre>
script.sh parameter-1 ... parameter-p input-1 ... input-i output-1 ... output-o
</pre>
See [[Eval operators]] for shell scripting or calling binaries.
h2. Operators
The operator are divided in three categories:
* [[Eval operators]] that directly execute the commands entered by Ariane.
* [[KDD operators]] are special components for calling Weka components or RapidMiner processes.
* [[Shell operators]] that directly execute the commands entered by Ariane.
h2. Pattern mining prototypes
KDAriane uses some specific prototypes:
* [[music-dfs]] : mining patterns under various constraints
* [[mtminer]] : levelwise minimal transversals of hypergraph
* [[mvminer]] : mining delta-free patterns in presence of missing values
h2. Routines
Routines are complex streams that Ariane allows you to share.
* [[shell routines]]
* [[routines for missing values ]]
* [[KDD routines]]
h2. To-do
* members/frioult/opposee : mtsminer 1 0 1 sample.bin sample.bin -> Segmentation fault (core dumped)
* sous-projet members
* unifier options mvminer
h2. Appendix
h3. Utilities
* [[gnuplot]]: plotting data with GNUplot
* [[score]] :
* [[complement]] :
* [[dictionary]] :
* [[segmentation]] :
h3. References