P
P Juszczak
Authored
13 records found
Sometimesnoveloroutlierdatahastobedetected.Theoutliersmayindicatesomeinterestingrareevent,ortheyshouldbedisregardedbecausetheycannotbereliablyprocessedfurther.Intheidealcasethattheobjectsarerepresentedbyverygoodfeatures,thegenuinedataformsacompactclusterandagoodoutliermeasureisth
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In one-class classification one tries to describe a class of target data and to distinguish it from all other possible outlier objects. Obvious applications are areas where outliers are very diverse or very difficult or expensive to measure, such as in machine diagnostics or in m
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When in a classification problem only samples of one class are easily accessible, this problem is called a one-class classification problem. Many standard classifiers, like backpropagation neural networks, fail on this data. Some other classifiers, like k-means clustering or near
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