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 KDAriane.


In the sample folder, KDAriane provides some examples of KDD scenarios:

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: 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 are complex streams that Ariane allows you to share.


  • sous-projet members
  • unifier options mvminer