KDD procedures


KDD procedures and modules

There are procedures for input data transformations, several data mining procedures based on the GUHA principle and machine learning procedure KEX. Some of procedures have additional modules.

LISp-Miner All-in-one
All-in-one installation file for the most used modules of the LISp-Miner system
LM Exec
LM Exec module for executing scripts in the LISp-Miner Control Language
LM GridPooler
Batch processing of tasks on the grid
LM Reverse-Miner
The Reverse-Miner module generates artificial data for educational and research purposes that could be later analysed in the usual way by the LISp-Miner system (or any other system for KDD).
Machine learning procedure KEX (Knowledge EXplorer) performs symbolic empirical multiple concept learning from examples, where the induced concept description is represented as a set of weighted decision rules.
Data transformation procedure TimeTransf computes various characteristics of time series. The resulting characteristics can be used as input of analytical procedures.