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Apriori Algorithm Tutorial

This document provides steps to implement the Apriori algorithm for association rule mining using the WEKA data mining tool. It describes opening a sample dataset, selecting the Apriori algorithm from the associate tab interface, and viewing the association rules generated when Apriori is applied to the dataset. The sample dataset contains attributes for admission year and course with data on student enrollments from 2005-2010.

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Milind Bhakta
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119 views3 pages

Apriori Algorithm Tutorial

This document provides steps to implement the Apriori algorithm for association rule mining using the WEKA data mining tool. It describes opening a sample dataset, selecting the Apriori algorithm from the associate tab interface, and viewing the association rules generated when Apriori is applied to the dataset. The sample dataset contains attributes for admission year and course with data on student enrollments from 2005-2010.

Uploaded by

Milind Bhakta
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as DOCX, PDF, TXT or read online on Scribd
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Practical 4

Date:AIM:- Implement Apriori Algorithm for Association Rule Mining.


This experiment illustrates some of the basic elements of association rule mining
using WEKA. The sample dataset used for this example is test.arff
Step1: Open the data file in Weka Explorer. It is presumed that the required data
fields have been discretized. In this example it is age attribute.
Step2: Clicking on the associate tab will bring up the interface for association rule
algorithm.
Step3: We will use apriori algorithm. This is the default algorithm.
Step4: Inorder to change the parameters for the run (example support, confidence
etc) we click on the text box immediately to the right of the choose button.
Dataset test.arff
@relation test
@attribute admissionyear {2005,2006,2007,2008,2009,2010}
@attribute course {cse,mech,it,ece}
@data
%
2005, cse
2005, it
2005, cse
2006, mech
2006, it
2006, ece
2007, it
Computer Science & Engineering Department, FETR, Isroli
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2007, cse
2008, it
2008, cse
2009, it
2009, ece
%
The following screenshot shows the association rules that were generated when
apriori algorithm is applied on the given dataset.

Computer Science & Engineering Department, FETR, Isroli


Page

Computer Science & Engineering Department, FETR, Isroli


Page

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