数据挖掘之异常检测.ppt

数据挖掘之异常检测.ppt

ID:52421020

大小:5.33 MB

页数:44页

时间:2020-04-06

数据挖掘之异常检测.ppt_第1页
数据挖掘之异常检测.ppt_第2页
数据挖掘之异常检测.ppt_第3页
数据挖掘之异常检测.ppt_第4页
数据挖掘之异常检测.ppt_第5页
资源描述:

《数据挖掘之异常检测.ppt》由会员上传分享,免费在线阅读,更多相关内容在行业资料-天天文库

1、AnomalyDetection:AintroductionSourceofslides:TutorialAtAmericanStatisticalAssociation(ASA2008)JiaweiHan-datamining:conceptsandtechniquesTutorialattheEuropeanConferenceonPrinciplesandPracticeofKnowledgeDiscoveryinDatabasesSpeaker:WentaoLiOutlineDefinitionApplicationMethodsLim

2、itedtime,SoIjustdrawthepictureofanomalydetection,formoredetail,pleaseturntothepaperforhelp.WhatareAnomalies?AnomalyisapatterninthedatathatdoesnotconformtotheexpectedbehaviorAnomalyisAdataobjectthatdeviatessignificantlyfromthenormalobjectsasifitweregeneratedbyadifferentmechan

3、ismAlsoreferredtoasoutliers,exceptions,peculiarities,surprises,etc.Anomaliestranslatetosignificant(oftencritical)reallifeentitiesCyberintrusionsCreditcardfraudFaultsinmechanicalsystemsRelatedproblemsOutliersaredifferentfromthenoisedataNoiseisrandomerrororvarianceinameasuredv

4、ariableNoiseshouldberemovedbeforeoutlierdetectionOutliersareinteresting:ItviolatesthemechanismthatgeneratesthenormaldataOutlierdetectionvs.noveltydetection:earlystage,outlier;butlatermergedintothemodelKeyChallengesDefiningarepresentativenormalregionischallengingTheboundarybe

5、tweennormalandoutlyingbehaviorisoftennotpreciseAvailabilityoflabeleddatafortraining/validationTheexactnotionofanoutlierisdifferentfordifferentapplicationdomainsDatamightcontainnoiseNormalbehaviorkeepsevolvingAppropriateselectionofrelevantfeaturesMapRelatedareas(theory)Applic

6、ation(practice)ProblemformulationDetectioneffect+AspectsofAnomalyDetectionProblemNatureofinputdataWhatisthecharacteristicofinputdataAvailabilityofsupervisionNumberoflabelTypeofanomaly:point,contextual,structuralTypeofanomalyOutputofanomalydetectionScorevslabelEvaluationofano

7、malydetectiontechniquesWhatkindofdetectionisgoodInputDataMostcommonformofdatahandledbyanomalydetectiontechniquesisRecordDataUnivariateMultivariateInputDataMostcommonformofdatahandledbyanomalydetectiontechniquesisRecordDataUnivariateMultivariateInputData–NatureofAttributesNat

8、ureofattributesBinaryCategoricalContinuousHybridcategoricalcontinuouscontin

当前文档最多预览五页,下载文档查看全文

此文档下载收益归作者所有

当前文档最多预览五页,下载文档查看全文
温馨提示:
1. 部分包含数学公式或PPT动画的文件,查看预览时可能会显示错乱或异常,文件下载后无此问题,请放心下载。
2. 本文档由用户上传,版权归属用户,天天文库负责整理代发布。如果您对本文档版权有争议请及时联系客服。
3. 下载前请仔细阅读文档内容,确认文档内容符合您的需求后进行下载,若出现内容与标题不符可向本站投诉处理。
4. 下载文档时可能由于网络波动等原因无法下载或下载错误,付费完成后未能成功下载的用户请联系客服处理。