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🔨 Python implementation of Apriori algorithm, new and simple!

Home Page: https://towardsdatascience.com/apriori-association-rule-mining-explanation-and-python-implementation-290b42afdfc6

License: MIT License

Python 100.00%

data-mining algorithms frequent-pattern-mining apriori apriori-algorithm python

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how to I infer "rules[0] --> rules[1], confidence = rules[2]" from the rules

First of all, thank you so much for this. This is comparatively computationally faster than the other implementations of Apirori I found on GitHub.

In the README, you have mentioned this sort of pattern

rules[0] --> rules[1], confidence = rules[2]

How do I infer this from the rules set?

Following are the first 3 rules generated from my run of apriori_python on a toy dataset:
[{'Apple'}, {'Orange'}, 0.5008052439747973] #rules[0]
[{'Grapes', 'Orange'}, {'Apple', 'Banana'}, 0.5056131260794473] #rules[1]
[{'Banana', 'Kiwi'}, {'Apple'}, 0.5072046109510087] #rules[2]

Also, what exactly is meant by rules[0] --> rules[1], confidence = rules[2] ?
Does it mean that when rules[0] is the antecedent then rules[1] is the consequent with a confidence mentioned against rules[1] that together forms the rules[2]?

Sorry for so many dumb questions, I'm still new to ARM modelling.

running command error

Hello, I am a newcomer learning python and data science, I don't know if this question is relatively simple and stupid, but I found that the running command of this code is incorrect.

➜  apriori_python git:(master) ✗ ls                               
__init__.py apriori.py  utils.py
➜  apriori_python git:(master) ✗ python3 apriori.py -f dataset.csv
Traceback (most recent call last):
  File "/Users/juanitahowe/Documents/GitHub/apriori_python/apriori_python/apriori.py", line 87, in <module>
    freqItemSet, rules = aprioriFromFile(options.inputFile, options.minSup, options.minConf)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/juanitahowe/Documents/GitHub/apriori_python/apriori_python/apriori.py", line 38, in aprioriFromFile
    C1ItemSet, itemSetList = getFromFile(fname)
                             ^^^^^^^^^^^^^^^^^^
  File "/opt/homebrew/lib/python3.11/site-packages/apriori_python/utils.py", line 32, in getFromFile
    with open(fname, 'r') as file:
         ^^^^^^^^^^^^^^^^
FileNotFoundError: [Errno 2] No such file or directory: 'dataset.csv'
➜  apriori_python git:(master) ✗ python3 apriori.py -f tesco2.csv -s 0.5 -c 0.5
Traceback (most recent call last):
  File "/Users/juanitahowe/Documents/GitHub/apriori_python/apriori_python/apriori.py", line 87, in <module>
    freqItemSet, rules = aprioriFromFile(options.inputFile, options.minSup, options.minConf)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/juanitahowe/Documents/GitHub/apriori_python/apriori_python/apriori.py", line 38, in aprioriFromFile
    C1ItemSet, itemSetList = getFromFile(fname)
                             ^^^^^^^^^^^^^^^^^^
  File "/opt/homebrew/lib/python3.11/site-packages/apriori_python/utils.py", line 32, in getFromFile
    with open(fname, 'r') as file:
         ^^^^^^^^^^^^^^^^
FileNotFoundError: [Errno 2] No such file or directory: 'tesco2.csv'

To run program with specific dataset, I think this is the correct command

➜  apriori_python git:(master) ✗ python3 apriori.py -f ../dataset/tesco2.csv -s 0.5 -c 0.5

chonyy / apriori_python Goto Github PK

apriori_python's Introduction

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apriori_python's Issues

how to I infer "rules[0] --> rules[1], confidence = rules[2]" from the rules

running command error

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