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).

KEX

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.

TimeTransf

Data transformation procedure TimeTransf computes various characteristics of time series. The resulting characteristics can be used as input of analytical procedures.