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nirvitarka avatar nirvitarka commented on June 19, 2024 1

Got it, thank you for helping

from efficient-apriori.

tommyod avatar tommyod commented on June 19, 2024

Hello @nirvitarka . Thank you for raising the issue.

You should change the filename. The min_support argument is set a too high, and so is min_confidence. This is data set dependent, and there is a trade-off between speed and output.

The following works for me:

from efficient_apriori import apriori

def data_generator(filename):
    def data_gen():
        with open(filename) as file:
            for line in file:
                yield tuple(k.strip() for k in line.split(','))
    
    return data_gen

transactions = data_generator('store_data.csv')

itemsets, rules = apriori(transactions, 
                          min_support=0.05, 
                          min_confidence=0.01, 
                          verbosity=2)

for rule in sorted(rules, key=lambda rule: rule.lift):
    print(rule)

Please note that the data generator approach is not needed when data fits into memory.

The following approach is better, since it loads data into memory once.

from efficient_apriori import apriori

# Read data into memory from the file
transactions = []
with open('store_data.csv') as file:
    for line in file:
        transactions.append(set(tuple(k.strip() for k in line.split(','))))

# Run the Apriori algorithm, print output with `verbosity`
itemsets, rules = apriori(transactions, 
                          min_support=0.05, 
                          min_confidence=0.01, 
                          verbosity=2)

for rule in sorted(rules, key=lambda rule: rule.lift):
    print(rule)

If hope this helps. Let me know if it works for you.

from efficient-apriori.

nirvitarka avatar nirvitarka commented on June 19, 2024

Thank you for prompt response.

I changed the filename as I used a subset of that data in "data.csv".
Changing min_support & min_confidence helped, it worked on a smaller subset of data.

However still not working on the original "store_data.csv". It says "Rule generation terminated." and ends.

It is getting some itemsets for length 1 & 2 & no itemsets of length 3.

Am I understanding it right that it should display results for length 1 & 2 itemsets?

from efficient-apriori.

tommyod avatar tommyod commented on June 19, 2024

That depends on whether you filter the rules or not, print(rules) will show all rules with no filtering. Depending on the data and the values for min_support and min_confidence, you might or might not have any rules of length 3 at all.

from efficient-apriori.

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