so4gp 0.0.3

Algorithm implementations of swarm-based optimization algorithms for mining gradual patterns.

SO4GP stands for: "Swarm Optimization for Gradual Patterns". SO4GP applies swarm intelligence to extraction of gradual patterns. It provides Python algorithm implementations of swarm-based optimization algorithms for mining gradual patterns. The algorithm implementations include:

• Ant Colony Optimization

Usage

Write the following code:

from so4gp_pkg import so4gp as so
gps = so.run_ant_colony('filename.csv', min_sup)
print(gps)

where you specify the parameters as follows:

• filename.csv - [required] a file in csv format
• min_sup - [optional] minimum support default = 0.5

Sample Output

{
  'Best Patterns': [
    [['Expenses-', 'Age+'], 1.0], 
    [['Expenses-', 'Age+', 'Salary+'], 0.6]
  ], 
  'Iterations': 100
}

References

• Owuor, D., Runkler T., Laurent A., Menya E., Orero J (2021), Ant Colony Optimization for Mining Gradual Patterns. International Journal of Machine Learning and Cybernetics.
• Dickson Owuor, Anne Laurent, and Joseph Orero (2019). Mining Fuzzy-temporal Gradual Patterns. In the proceedings of the 2019 IEEE International Conference on Fuzzy Systems (FuzzIEEE). IEEE. https://doi.org/10.1109/FUZZ-IEEE.2019.8858883.