From 0c1bec381149b52ec2917501a0ac5bd95f7f4da9 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?aaron=20garcia=20mu=C3=B1iz?= Date: Tue, 26 Sep 2023 18:13:27 +0200 Subject: [PATCH] readme update --- readme.md | 40 ++++++++++++++++++++++++---------------- 1 file changed, 24 insertions(+), 16 deletions(-) diff --git a/readme.md b/readme.md index 9264276..4025d47 100644 --- a/readme.md +++ b/readme.md @@ -1,22 +1,30 @@ -IGSD -This repository contains the material refering to the paper: "", it contains: - 1. datasets: Directory in which datasets to be used in the algortihm are stored. - 2. results: Directory in which the algortihm will store the results produced. - 3. pysubgroup_mod: The project code. +# IGSD - Information Gained Subgroup Discovery Algorithm -1. IGSD Project Scripts -Contains the scripts of IGSD and other algorithms such as BeamSearch, DFS, BestFirstSearch, etc. Moreover, main.py is the -principal script file which will launch the specific algorithm. +This repository contains the implementation of IGSD: A new algorithm for Subgroup Set Discovery based on Information Gained, it contains: +1. pysubgroup_mod: The project code. +2. results: Directory in which the algortihm will store the results produced. +3. datasets: Directory in which datasets to be used in the algortihm are stored. + + +# 1. IGSD Project Scripts +Inside the folder pysubgroup_mod you can find the scripts of IGSD and other useful scripts. +Moreover, main.py is the principal script in charge of executing the main approach. + +# 2. Execution commands The main.py file required several arguments to be used, so the following command line will execute the python file: -py --dataname --class_column --class_value --mode --depth --list_ignore --list_conds + + +```py --dataname --class_column --class_value --mode --depth --list_ignore --list_conds ``` + With: - - : The name of the dataset input file. - - : The attribute (column) used as target (studied class). - - : The value of that we want to analize. - - : The mode that IGSD will employ to perfom the analysis when IG threshold is calculated (dynamic, maximum). If you want to employ another algorithm, the default value is used. - - : The number of attributes that the algortihms will consider. - - : A list with the attributes (columns) of the dataset that the user does not want to be consider in the anaylis. - - : A list with the attributes (columns) of the dataset that the user wants to be present in the patterns obtained. +* ``````: The name of the dataset input file. +* ``````: The attribute (column) used as target (studied class). +* ``````: The value of that we want to analize. +* ``````: The mode that IGSD will employ to perfom the analysis when IG threshold is calculated (dynamic, maximum). If you want to employ another algorithm, the default value is used. +* ``````: The number of attributes that the algortihms will consider. +* ``````: A list with the attributes (columns) of the dataset that the user does not want to be consider in the anaylis. +* ``````: A list with the attributes (columns) of the dataset that the user wants to be present in the patterns obtained. + -- 2.24.1