Algorithms

General usage from command line: python fileName.py <dataset.csv>

apriori-original.py

Generate all frequent itemsets based on MINSUP Generate association rules based on MINCONF

apriori-dominance.py

Generate -frequent itemsets and above based on MINSUP, then use dominance to prune this frequent itemset

apriori-contingencyDominance.py

Construct a contingency table when generating -frequent itemsets and above based on MINSUP, then use dominance to prune this frequent itemset

Datasets

data1.csv

https://archive.ics.uci.edu/dataset/352/online+retail After preprocessing has 1349 rows with (Avg: 18.8 items per transaction), 2337 unique items

data2.csv

https://archive.ics.uci.edu/dataset/502/online+retail+ii After preprocessing has 2138 rows with (Avg: 19.7 items per transaction), 3232 unique items

data3.csv

https://www.kaggle.com/datasets/irfanasrullah/groceries After preprocessing has 9835 rows with (Avg: 4.4 items per transaction), 331 unique items