Skip to content

A python implementation of the Multiple Support Apriori Algorithm

Notifications You must be signed in to change notification settings

ElefHead/frequent-itemset-miner

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

22 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Frequent Itemset Miner

A python implementation of the Multiple Support Apriori Algorithm

This implementation is based on the algorithm described in the book Web Data Mining by Prof. Bing Liu


Brief Description

preprocess.py - Handles converting the params and transaction lines into usable formats.
fileoperator.py - Handles all the reading and writing.
MSApriori.py - where main resides. Where the actual algorithm is implemented.


To Run Code

Please make sure that this is your folder structure (where the code resides)

Directory Structure

Inside MSApriori.py, line 39 : You can specify where your data resides. It is relative to the current directory.
Same way for params and results. If there is no results directory, the code will create one with the name as specified in this line.


Feeding Data

This code can work on data specified in multiple files, multiple sets of parameters and generate relevant results based on the data and params.
This is done by naming the data appropriately. Any file of the form data1.txt, data1-1.txt, basically data(N)(-M?).txt will be considered as one dataset N.
The corresponding params have to be specified as params(N)-(M).txt.

Please see data2/, params2/, and results2/ for example.

To run the code on data2/ and params2/ , please change line 39 from

f = FileOperator(datapath="./",data="data",params="params",results="results")  

to

f = FileOperator(datapath="./",data="data2",params="params2",results="results2")

and delete the results2/ folder(or move it) because the files won't be written over, the outputs will be appended.

There were some basic assumptions made as to how the data will be presented to the code. To test custom data, please use the given data and params files as example input formats.

Releases

No releases published

Packages

No packages published

Languages