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  <event:Event rdf:about="http://ebiquity.umbc.edu/event/html/id/171/Cost-Sensitive-Classifier-Evaluation-Using-Cost-Curves">
    <rdfs:label><![CDATA[Cost-Sensitive Classifier Evaluation Using Cost Curves]]></rdfs:label>
    <event:title><![CDATA[Cost-Sensitive Classifier Evaluation Using Cost Curves]]></event:title>
    <event:speaker><person:Collaborator rdf:about="http://ebiquity.umbc.edu/person/html/Robert/Holte/"><person:name><![CDATA[Robert  Holte]]></person:name><rdfs:label><![CDATA[Robert  Holte]]></rdfs:label></person:Collaborator></event:speaker>
    <event:startDate rdf:datatype="&xsd;dateTime">2006-09-28T10:00:00-05:00</event:startDate>
    <event:endDate rdf:datatype="&xsd;dateTime">2006-09-28T11:00:00-05:00</event:endDate>
    <event:location><![CDATA[325b]]></event:location>
    <event:abstract><![CDATA[The evaluation of classifier performance in a cost-sensitive setting is 
straightforward if the operating conditions (misclassification costs and 
class distributions) are fixed and known. When this is not the case, 
evaluation requires a method of visualizing classifier performance 
across the full range of possible operating conditions. This talk argues 
that the classic technique for classifier performance visualization -- 
the ROC curve – is inadequate for the needs of researchers and 
practitioners in several important respects. It then describes a 
different way of visualizing classifier performance -- the cost curve -- 
that overcomes these deficiencies. No familiarity with ROC curves or 
cost curves is necessary, they will be fully explained.]]></event:abstract>
    <event:tag><![CDATA[learning]]></event:tag>
    <event:tag><![CDATA[visualization]]></event:tag>
    <event:tag><![CDATA[hci]]></event:tag>
    <event:host><person:Collaborator rdf:about="http://ebiquity.umbc.edu/person/html/Marie/desJardins/"><person:name><![CDATA[Marie  desJardins]]></person:name><rdfs:label><![CDATA[Marie  desJardins]]></rdfs:label></person:Collaborator></event:host>
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