ARMADA Data Mining Tool version 1.3.2

An association rule data mining tool for experimentation and analysis.

Description

Association rules are a simple but very useful form of data mining that describe the probabilistic co-occurrence of certain events within a database. They were originally designed to analyse market-basket data, in which the likelihood of items being purchased together within the same transaction were analysed.

In the ARMADA tool (Association Rule Mining And Deduction Analysis) the rules are presented in the form of;

Item1, ItemN => ItemX

The rule is evaluated using two numerical measures.

SUPPORT: The number of occurrences, within the data set, of all components of an association rule occurring within a single transaction (a transaction can be thought of as a row in a conventional database).

CONFIDENCE: This is the probability that, given the antecedent (left hand side of the rule) being true, the consequent (right hand side) is true.

ARMADA contains several visualisation techniques for analysing quantative and qualative measures of each rule, as well as several strategies for undertaking data mining which can be used as exclusive or combinatorial methods.

To run GUI version type ARMADA in command line. Note: Requires MATLAB v5.2 to run.

Homepage:
http://www.aiai.ed.ac.uk/~jmalone

• MATLAB release: MATLAB 6.0 (R12)

Other Files

alterRateMenu.m,
ARMADA User Manual.pdf,
builderAddToRule.m,
builderNewRule.m,
calculateConfidence.m,
changeConfSlider.m,
changeRuleAnalysisDisplay.m,
changeRuleDisplay.m,
checkIfGoal.m,
checkIfLHSGoal.m,
clearAntRules.m,
clearConRules.m,
clearOneAntRule.m,
clearOneConRule.m,
closeAnalysisDisplay.m,
closeDisplay.m,
countInstance.m,
displayAbout.m,
displayAnalysisConfGraph.m,
displayAnalysisRuleGraph.m,
displayAnalysisRuleLine.m,
displayAnalysisRules.m,
displayAnalysisSupportGraph.m,
displayConfGraph.m,
displayRuleGraph.m,
displayRuleLine.m,
displayRules.m,
displaySupportGraph.m,
displayTopic.m,
evaluateCriteria.m,
exitProgram.m,
exitProgramSave.m,
exitProgramSaveDual.m,
gen1RHS.m,
gen1RHSWithGoal.m,
genMultiCand.m,
genRuleVariants.m,
genRuleVariantsWithGoal.m,
genTwoCand.m,
getLHSCount.m,
helpContents.m,
loadMiningResults.m,
lottery.txt,
openDataFile.m,
orderByLHS.m,
orderBySupConf.m,
orderRules.m,
performGoalMining.m,
performGoalMiningAnalysis.m,
performMining.m,
performMiningAnalysis.m,
printAnalysisRules.m,
printPausedAnalysisRules.m,
printPausedRules.m,
printRules.m,
Read Me.txt,
readFirstLine.m,
removeRules.m,
ruleBuilder.m,
sampleDataSet.m,
saveMiningResults.m,
saveMiningResultsDual.m,
saveRuleBuilder.m,
testdata.txt,
viewGoals.m,
alterConfBox.m,
genOneCand.m,
ARMADA.M

[Greg Y. Smith]

Good analysis methods and graphs. Perhaps future version for text would be useful?

[wu xiaojing]

 

[malay wang]

This tool is great. It is simple and convinent. If its future version can show the temp result of Apirioi,FP-tree,,,'s progress will be even great.

[hanaa alnajar]

 

[alejandro delphin]

 

[Hüseyin OCAK]

It is a simple tools for starters. It has visual advantages of MatLab against other Association Rule Tools. It can work only on numerical attributes. You can only change minimum support and minimum confidence values, but you can build rule goals to seek Armada for. Also you can take samples from the dataset in order to decrease the computation time, which may cause misleading results.

[zc wang]

ok! Let me try!

[zc w]

It doesn't work.

[my hu]

It work.

But how ?

[mod cat]

 

[realen wang]

ok

[Wang HQ]

Good !

[xcxc xcxc]

 

[Keshri Verma]

 

[ajit majumder]

 

[khanchel riadh]

 

[Wei Luo]

It does not work under Matlab 7.1.0.183 (R14) Service Pack 3.

[nancy jane]

 

[suresh pon]

 

[he weisong]

 

[Bayu AT]

nice tools, very helpful!