Wednesday, 12 April 2023

Apriori Algorithm

 import numpy as nm

import matplotlib.pyplot as mtp  
import pandas as pd 
from apyori import apriori  
import urllib.request

url="http://localhost/web/hupaddpairs.php?item1="

dataset = pd.read_csv('item_set1.csv')  
transactions=[]  
for i in range(0, 32):
    transactions.append([str(dataset.values[i,j])  for j in range(0,5)]) 

vals=""
rules= apriori(transactions= transactions, min_support=0.003, min_confidence = 0.2, min_lift=3, min_length=2, max_length=2) 
results= list(rules)  
for item in results:
    pair = item[0]   
    items = [x for x in pair]  
    print("Rule: " + items[0] + " -> " + items[1])  
    print("Support: " + str(item[1]))  
    print("Confidence: " + str(item[2][0][2]))  
    print("Lift: " + str(item[2][0][3]))  
    print("=====================================")  
    vals=url+items[0]+"&item2="+items[1]
    print(vals)
    webUrl = urllib.request.urlopen(vals)
    vals=""

-------------------
Data
item_set1.csv

electronics.smartphone,	electronics.video.tv			
electronics.smartphone,	electronics.video.tv,appliances.kitchen.washer		
electronics.smartphone,	electronics.audio.headphone			
electronics.audio.headphone,electronics.smartphone	appliances.environment.vacuum,kids.skates