gsppy 1.1

GSP (Generalized Sequence Pattern) algorithm in Python

GSP-Py

Generalized Sequence Pattern (GSP) algorithm in Python

This package was created to use GSP with Python

Table of Contents

• Requirements
• Installation
• Usage
• License
• Citation

Requirements

Install Python:

sudo apt install python3

Installation

To download GSP-Py just clone the Git repository hosted in GitHub:

git clone https://github.com/jacksonpradolima/gsp-py.git
python setup.py install

Alternatively, you can install it with pip:

pip install gsppy

Usage

Examples of configuring and running are located in the test folders gsppy folder.

To use it in a project, import it and use the GSP class.

from gsppy.gsp import GSP

It is assumed that your transactions are a sequence of sequences representing items in baskets.

 transactions = [
            ['Bread', 'Milk'],
            ['Bread', 'Diaper', 'Beer', 'Eggs'],
            ['Milk', 'Diaper', 'Beer', 'Coke'],
            ['Bread', 'Milk', 'Diaper', 'Beer'],
            ['Bread', 'Milk', 'Diaper', 'Coke']
        ]

Init the class to prepare the transactions and to find patterns in baskets that occur over the support threshold (count):

result = GSP(transactions).search(0.3)

The support count (or simply support) for a sequence is defined as the fraction of total data-sequences that "contain" this sequence. (Although the word "contains" is not strictly accurate once we incorporate taxonomies, it captures the spirt of when a data-sequence contributes to the support of a sequential pattern.)

License

This project is licensed under the terms of the MIT - see the LICENSE file for details.

Citation

If this package contributes to a project which leads to a scientific publication, I would appreciate a citation.

@misc{pradolima_gsppy,
  author       = {Prado Lima, Jackson Antonio do},
  title        = {{GSP-Py - Generalized Sequence Pattern algorithm in Python}},
  month        = jul,
  year         = 2019,
  doi          = {10.5281/zenodo.3333988},
  url          = {https://doi.org/10.5281/zenodo.3333988}
}