pip install apriori_python
Then use it like
from apriori_python import apriori itemSetList = [['eggs', 'bacon', 'soup'], ['eggs', 'bacon', 'apple'], ['soup', 'bacon', 'banana']] freqItemSet, rules = apriori(itemSetList, minSup=0.5, minConf=0.5) print(freqItemSet) print(rules) # [[{'beer'}, {'rice'}, 0.6666666666666666], [{'rice'}, {'beer'}, 1.0]] # rules[0] --> rules[1], confidence = rules[2]
Get a copy of this repo using git clone
git clone https://github.com/chonyy/apriori_python.git
Run the program with dataset provided and default values for minSupport = 0.5 and minConfidence = 0.5
python apriori.py -f dataset.csv
Run program with dataset and min support and min confidence
python apriori.py -f ../dataset/tesco2.csv -s 0.5 -c 0.5
- Support: Fraction of transactions that contain an itemset
- Confidence: Measures how often items in Y appear in transactions that contain X
- Frequent itemset: An itemset whose support is greater than or equal to a minSup threshold