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Python implementation of the Frequent Pattern Growth algorithm

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OS: Ubuntu 16.04 64bit fpgrowth version 1.0, installed by pip install pyfpgrowth in virtualenv python3.5 I want use pyfpgrowth to mining trajectory latitude data, such as 41.804068 41.802275 41.802275 41.802383...

Is there some way to extract antecedent and consequent from the rules...??

This pull request aims to close issues #3, #6, #11, #12 and #15. The function `generate_association_rules(...)` is revised in the following ways: 1. The return value is changed to a...

Hi All, In working on this issue for my own work I found a problem with the generate_association rules module specifically with the line below **if confidence >= confidence_threshold: rules[antecedent]...

This function can trivially be rewritten to avoid recursion: https://github.com/evandempsey/fp-growth/blob/6bf4503024e86c5bbea8a05560594f2f7f061c15/pyfpgrowth/pyfpgrowth.py#L109-L133 Rather than recurse, loop over the items: ```python def insert_tree(self, items, node, headers): """Grow FP tree iteratively""" for item in...

missing itemsets in patterns. Also plz add ` LIft` to filter rules.

In generating an association rule, lower support should also be larger than a threshold.

`import pyfpgrowth item_list = [[11, 13], [4, 12, 13], [4, 13, 14, 17], [7, 11, 13, 14, 17], [2, 4, 13, 14], [13, 14], [2, 7, 11, 13, 14], [4,...

Frequency for only one element is not counted in function zip_patterns. It can be fixed by adding frequency of root in the return value of that function. Btw really nice...