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.
You can watch the short demonstration of KDAriane.
You can read the document Data preparation for a first contact with
KDArianeprovides 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 
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 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:
script.sh parameter-1 ... parameter-p input-1 ... input-i output-1 ... output-o
See Eval operators for shell scripting or calling binaries.
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.
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
Routines¶Routines are complex streams that Ariane allows you to share.
- sous-projet members
- unifier options mvminer
- gnuplot: plotting data with GNUplot
- score : computing validation values from a decision file
- complement :
- dictionary :
- segmentation :