基于二維表的關(guān)聯(lián)規(guī)則挖掘研究

1、中國民航大學(xué)碩士學(xué)位論文基于二維表的關(guān)聯(lián)規(guī)則挖掘研究姓名：孟維芬申請學(xué)位級別：碩士專業(yè)：計算機(jī)應(yīng)用技術(shù)指導(dǎo)教師：劉山20080406中國民航大學(xué)碩上學(xué)位論文AbstractMiningforassociationrulesisanimportantclassofdataminingTheoverallperformanceofminingassociationrulesisdeterminedbyfindingallfrequentit

2、emsetsClassicminingalgorithms，suchasApriori，F(xiàn)PGrowtharepresentedApriorimaysufferfromnontrivialcosts：ItmayneedtorepeatedlyscanthedatabaseandcheckalargesetofcandidatesbypatternmatchingFPGrowthisamainmemory—basedalgorithmIt

3、sdisadvantageis：Whenthedatabaseislarge，itsFP—treecannotfitinmainmemoryTheexistingalgorithmsneglecttransactionforsupportingfrequentitemsetsAccordingtothelimitationoftheexistingalgorithm，thepaperputsforwardarithmeticnamedb

4、asedonprefixaltemationforcalculatingfrequentpatterns，includingstaticanddynamic，basedon2DimensiontableThealgorithmcompressedtransactiondatabaseintodatabaseavoidingrepeatedlyscanthedatabaseBecauseresultsincludeconcretetran

5、sactionscangetinterestingfrequentitemsetsthroughsettingtimebaseFormeetingmin_sup’SfrequentitemsetsCananalysistimeattributetogetsteadyandunsteadyclassesInthesameconditions，the20x20matrixhasmaindiagonalelements0andtheother

6、s1，F(xiàn)PGrowthalgorithmwillnotbeabletohandleThisarithmeticisusedtoanalyzethedatafromaviationaccidentAtlast，wediscussthedisadvantageofthealgorithmWiththedeepresearchofthisproject，thealgorithmwillhaveabrightfutureKeyWordsData