dmdarkness/data-mining

Some algorithms to form frequent itemsets/association rules from datasets, where many techniques, such as FP-tree, Apriori, PSO, GA, Granular computing, Central limit theorem and so on, are applied

Data-mining

Some algorithms to form frequent itemsets/association rules from datasets, where many techniques, such as FP-tree, Apriori, PSO, GA, Granular computing, Central limit theorem and so on, are applied

For Python 2.7

Usage

Any .pyd can be put in the working directory and be imported by Python, which is also implemented by c++. The details of usage can be found in How to use.py.

Algorithms

1. FP-Growth: pyfpgrowth.pyd is the corresponding .pyd.
2. FPtorules: a function to form association rules from frequent patterns, FPtorules.py is the corresponding implementation.
3. BPSO-HD: A BPSO (Binary Particle Swarm Optimization) based algorithm mining long frequent patterns. pybpsohd.pyd is the corresponding .pyd. This is the corresponding paper
4. CLT: A Central Limit Theorem based algorithm mining frequent patterns. pyclt.pyd is the corresponding .pyd.
5. ARMGA: A GA (Genetic Algorithm) based algorithm mining association rules. pyarmga.pyd is the corresponding .pyd.