Documentation » Historique » Révision 28
Révision 27 (François Rioult, 03/02/2011 19:55) → Révision 28/37 (François Rioult, 03/02/2011 20:46)
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. 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] * [[CAEP]]: supervised classification with emerging patterns [2] * experiences about perturbation on training and test file with Weka classifiers and RapidMiner processes. 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. h2. How is KDAriane working? 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-2 ... parameter-p input-1 input-2 ... input-i output-1 output-2 ... output-o </pre> See [[Special operators for shell scripting]] for more details. h2. Operators The operator are divided in three two categories: * [[Shell 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 h2. Scenarios KDAriane provides some examples of KDD realized through Ariane: * [[mvminer]] : [[Data preparation]]: a first scenario for the binarization of CSV data. * [[Data mining delta-free complexity]]: pattern mining and complexity visualization * [[CMAR]]: supervised classification with association rules [1] * [[CAEP]]: supervised classification with emerging patterns in presence of missing values [2] * experiences about perturbation on training and test file with Weka classifiers and RapidMiner processes. h2. Routines Routines are complex streams that Ariane allows you to share. * [[shell routines]] * [[KDD routines]] h2. Appendix h3. Utilities * [[gnuplot]]: plotting data with GNUplot * [[score]] : * [[complement]] : * [[dictionary]] : * [[segmentation]] : h3. References