Documentation » Historique » Révision 34
Révision 33 (François Rioult, 19/09/2012 19:20) → Révision 34/37 (François Rioult, 18/11/2012 17:29)
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