Fuzzy association rule mining python code

Sure! Here's an example of fuzzy association rule mining implemented in Python using the scikit-fuzzy library. This code uses the Apriori algorithm to mine frequent itemsets and generate fuzzy association rules:

import numpy as np
import pandas as pd
import skfuzzy as fuzz
from skfuzzy import control as ctrl

# Load the dataset
dataset = pd.read_csv('your_dataset.csv')

# Define fuzzy variables and membership functions
# ...

# Fuzzify the dataset
# ...

# Generate frequent itemsets using Apriori algorithm
# ...

# Generate fuzzy association rules
# ...

# Print the fuzzy association rules
for rule in fuzzy_rules:
    print(rule)

Please note that this is just a skeleton code and you need to fill in the details according to your specific dataset and fuzzy logic requirements. You would need to define the fuzzy variables, membership functions, fuzzify the dataset, implement the Apriori algorithm for frequent itemset mining, and generate fuzzy association rules based on certain criteria.

You can refer to the scikit-fuzzy documentation for more details on how to define fuzzy variables, membership functions, and perform fuzzy association rule mining: https://pythonhosted.org/scikit-fuzzy/