◤KDD procedures – CF-Miner◢
Main menu:
Milan Šimůnek, Jan Rauch
Jan Rauch (theory), Milan Šimůnek (software), Martin Kejkula (help)
Data mining procedure Cf-Miner mines for patterns of the form (~ R) / Cond. Here R is a categorial attribute with categories r_{1}, …, r_{K} and Cond is a Boolean attribute.
The procedure deals with data matrices. The attribute R corresponds to a column of the analysed data matrix. Boolean attribute Cond is derived from the other columns of the data matrix.
The intuitive meaning of the pattern (~ R) / Cond is that the categories of the attribute R satisfy the condition given by the symbol ~ for the subset of rows of analysed data matrix defined by the Boolean attribute Cond.
The symbol ~ is called CF-quantifier. It corresponds to a condition imposed on the vector of frequencies of particular categories of the attribute R. The pattern (~ R) / Cond is verified on the data matrix M / Cond. Here M is the analysed data matrix and M / Cond is a data matrix consisting of all rows of M satisfying Cond.
LISp-Miner.Core.OldUI.zip | 33.45 MB | August 13, 2014 |
Legacy LISp-Miner system core files separated into modules for each GUHA procedure. Contains also other legacy modules LMAdmin and LMDataSource. |
The procedure Cf-Miner was suggested by J. Rauch in 2002. Reason was the necessity to mine for patterns describing a distribution of frequencies of a categorial attribute. The second reason was the possibility to use the software tools for dealing with strings of bits developed for the 4ft-Miner procedure. The suggestion was published under name Pareto-Miner in [RS 02].
The first version of the procedure with set of simple CF-quantifiers was implemented by M. Šimůnek.
Main menu:
Send comments about this site to the webmaster