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Python Implementation of Apriori Algorithm for finding Frequent sets and Association Rules

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Python Implementation of Apriori Algorithm

List of files

  1. apriori.py
  2. INTEGRATED-DATASET.csv
  3. README(this file)

The dataset is a copy of the “Online directory of certified businesses with a detailed profile” file from the Small Business Services (SBS) dataset in the NYC Open Data Sets

Usage

To run the program with dataset provided and default values for _minSupport_(0.15) and *minConfidence*(0.6)

python apriori.py -f INTEGRATED-DATASET.csv

To run program with dataset

python apriori.py -f INTEGRATED-DATASET.csv -s 0.17 -c 0.68

Best results are obtained for the following values of support and confidence:

Support : Between 0.1 and 0.2

Confidence : Between 0.5 and 0.7

License

MIT-License

Disclaimer

I do not actively work on this. Suggestions to improve are however welcome.

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Python Implementation of Apriori Algorithm for finding Frequent sets and Association Rules

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