ml-finance-python

apriori.py

(1178B)

 from __future__ import division, print_function
 import numpy as np
 
 from mlfromscratch.unsupervised_learning import Apriori
 
 def main():
     # Demo transaction set
     # Example 2: https://en.wikipedia.org/wiki/Apriori_algorithm
     transactions = np.array([[1, 2, 3, 4], [1, 2, 4], [1, 2], [2, 3, 4], [2, 3], [3, 4], [2, 4]])
     print ("+-------------+")
     print ("|   Apriori   |")
     print ("+-------------+")
     min_sup = 0.25
     min_conf = 0.8
     print ("Minimum Support: %.2f" % (min_sup))
     print ("Minimum Confidence: %s" % (min_conf))
     print ("Transactions:")
     for transaction in transactions:
         print ("\t%s" % transaction)
 
     apriori = Apriori(min_sup=min_sup, min_conf=min_conf)
 
     # Get and print the frequent itemsets
     frequent_itemsets = apriori.find_frequent_itemsets(transactions)
     print ("Frequent Itemsets:\n\t%s" % frequent_itemsets)
 
     # Get and print the rules
     rules = apriori.generate_rules(transactions)
     print ("Rules:")
     for rule in rules:
         print ("\t%s -> %s (support: %.2f, confidence: %s)" % (rule.antecedent, rule.concequent, rule.support, rule.confidence,))
 
 
 if __name__ == "__main__":
     main()