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    <header>
        <corpus description="BNC2" name="BNC2" ID="111">
            <document description="bncp" name="bncp" ID="421"/>
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        <frame>
            <FE fgColor="FFFFFF" bgColor="FF69B4" type="Core" abbrev="Task" name="ML_Task"/>
            <FE fgColor="FFFFFF" bgColor="004C99" type="Peripheral" abbrev="Algorithm" name="ML_Algorithm"/>
        </frame>
    </header>
    <definition>This is a frame for representing ML Task, and optionally an algorithm for solving it.</definition>
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            <text>Supervised learning can be used to build class probability estimates.</text>
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        <sentence corpID="111" docID="421" sentNo="2" paragNo="181" aPos="0" ID="1215438">
            <text>The first two are not conceptually different from the point of view of Reinforcement Learning.</text>
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        <sentence corpID="111" docID="421" sentNo="3" paragNo="181" aPos="0" ID="1215438">
            <text>The successful application of these genetic algorithms to supervised learning problems sets the stage for the use of genetic algorithms in reinforcement learning problems.</text>
            <annotationSet cDate="05/02/2003 04:00:38 PDT Fri" status="MANUAL" ID="1877967">
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        <sentence corpID="111" docID="421" sentNo="4" paragNo="181" aPos="0" ID="1215438">
            <text>In this paper, we proposed a generic framework called RCE for estimating the feature importance in unsupervised learning, using an ensemble of clustering algorithms.</text>
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        </sentence>
        <sentence corpID="111" docID="421" sentNo="5" paragNo="181" aPos="0" ID="1215438">
            <text>Our framework decouples classification and active learning.</text>
            <annotationSet cDate="05/02/2003 04:00:38 PDT Fri" status="MANUAL" ID="1877967">
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                    <label end="0" start="0" name="10.1007/s10994-015-5504-1"/>
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        <sentence corpID="111" docID="421" sentNo="6" paragNo="181" aPos="0" ID="1215438">
            <text>For supervised feature selection, it also supports both regression and classification.</text>
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                <layer rank="1" name="Target">
                    <label end="0" start="0" name="10.1007/978-3-642-33460-3_21"/>
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        <sentence corpID="111" docID="421" sentNo="7" paragNo="181" aPos="0" ID="1215438">
            <text>To fulfill our given clustering task, the algorithm must derive a dendrogram that reflects the underlying hierarchy as much as possible.</text>
            <annotationSet cDate="05/02/2003 04:00:38 PDT Fri" status="MANUAL" ID="1877967">
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        <sentence corpID="111" docID="421" sentNo="8" paragNo="181" aPos="0" ID="1215438">
            <text>Although it is understood that unsupervised learning is more difficult than supervised learning, there is a need for an effective learning method for density estimation.</text>
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        <sentence corpID="111" docID="421" sentNo="9" paragNo="181" aPos="0" ID="1215438">
            <text>In subspace clustering, objects may participate in multiple clusters across multiple subspaces.</text>
            <annotationSet cDate="05/02/2003 04:00:38 PDT Fri" status="MANUAL" ID="1877967">
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task_corpus.txt · Last modified: 2016/03/16 13:57 by pj