Book a Demo!
CoCalc Logo Icon
StoreFeaturesDocsShareSupportNewsAboutPoliciesSign UpSign In
debakarr
GitHub Repository: debakarr/machinelearning
Path: blob/master/Part 5 - Association Rule Learning/Apriori/apriori.py
1339 views
1
# Apriori
2
3
# Importing the libraries
4
import numpy as np
5
import matplotlib.pyplot as plt
6
import pandas as pd
7
8
# Data Preprocessing
9
dataset = pd.read_csv('Market_Basket_Optimisation.csv', header = None)
10
transactions = []
11
for i in range(0, 7501):
12
transactions.append([str(dataset.values[i,j]) for j in range(0, 20)])
13
14
# Training Apriori on the dataset
15
from apyori import apriori
16
rules = apriori(transactions, min_support = 0.003, min_confidence = 0.2, min_lift = 3, min_length = 2)
17
18
# Visualising the results
19
results = list(rules)
20