Commit 0c1bec38 authored by aaron garcia muñiz's avatar aaron garcia muñiz

readme update

parent 392f8fe9
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 <FILE> --class_column <CLASS_COLUMN> --class_value <CLASS_VALUE> --mode <MODE> --depth <DEPTH> --list_ignore <LIST_IGNORE> --list_conds <LIST_CONDS>
```py --dataname <FILE> --class_column <CLASS_COLUMN> --class_value <CLASS_VALUE> --mode <MODE> --depth <DEPTH> --list_ignore <LIST_IGNORE> --list_conds <LIST_CONDS>```
With:
- <FILE>: The name of the dataset input file.
- <CLASS_COLUMN>: The attribute (column) used as target (studied class).
- <CLASS_VALUE>: The value of <CLASS_COLUMN> that we want to analize.
- <MODE>: 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.
- <DEPTH>: The number of attributes that the algortihms will consider.
- <LIST_IGNORE>: A list with the attributes (columns) of the dataset that the user does not want to be consider in the anaylis.
- <LIST_CONDS>: A list with the attributes (columns) of the dataset that the user wants to be present in the patterns obtained.
* ```<FILE>```: The name of the dataset input file.
* ```<CLASS_COLUMN>```: The attribute (column) used as target (studied class).
* ```<CLASS_VALUE>```: The value of <CLASS_COLUMN> that we want to analize.
* ```<MODE>```: 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.
* ```<DEPTH>```: The number of attributes that the algortihms will consider.
* ```<LIST_IGNORE>```: A list with the attributes (columns) of the dataset that the user does not want to be consider in the anaylis.
* ```<LIST_CONDS>```: A list with the attributes (columns) of the dataset that the user wants to be present in the patterns obtained.
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